Reviewerly/exHarmony huggingface dataset:
Exploring Students’ Readiness in context of Transformation from Traditional to Online Teaching Practices at Higher Education Institutions

This study analyzed students 'perceived readiness at Higher Education Institutions in Pakistan.A quantitative approach was used to collect data through survey method from 368 students (151 males and 217 females) from five public sector Higher education institutions of South Punjab, Pakistan.The scale adopted in this study Online Learning Readiness (OLRS) was designed by Hung et al. (2010).The gathered data was analyzed by using SPSS.The collected data revealed that students were highly prepared for online learning and were successful and confident in their online educational endeavors.However, a significant difference was observed in opinion of male and female respondents on five dimensions of scale.In present study, male students exhibited more readiness than female students.These findings will help institutions and teachers with providing further training to improve students' digital skills, ensuring the improvement of learning practices in new online environments, and implementing guidelines and policies.
SOME PROBLEMS OF GENERAL EDUCATION CONTENT

This article is devoted to debatable issues regarding the sources, principles, rules, stages, and methodology for selecting and designing the content of education. The selection and placement of the content of education in the curriculum and textbooks requires going through the filter of didactic, psychological, hygienic, and other theoretical and normative approaches in human, socio-human, and social sciences. The research presents a model for analyzing the training-development activity of the educational content's attitude component.
Hate speech, Censorship, and Freedom of Speech: The Changing Policies of Reddit

This paper examines the shift in focus on content policies and user attitudes on the social media platform Reddit. We do this by focusing on comments from general Reddit users from five posts made by admins (moderators) on updates to Reddit Content Policy. All five concern the nature of what kind of content is allowed to be posted on Reddit, and which measures will be taken against content that violates these policies. We use topic modeling to probe how the general discourse for Redditors has changed around limitations on content, and later, limitations on hate speech, or speech that incites violence against a particular group. We show that there is a clear shift in both the contents and the user attitudes that can be linked to contemporary societal upheaval as well as newly passed laws and regulations, and contribute to the wider discussion on hate speech moderation.
Comparative Analysis and Performance Evaluation of Cryptographic Algorithms

Encryption, which is based on the science of cryptography, is required to protect data and information in computer networks. As computing overhead rises, available encryption techniques are put to the test. It is necessary to assess the encryption algorithms’ performance in order to establish their applicability for various security scenarios and applications. The findings of available research on comparison studies and performance evaluation of encryption algorithms are inconsistent, therefore the authors could not draw any conclusions about the encryption algorithms’ performance based on different metrics. Three of the most widely debated encryption algorithms, Rivest, Shamir, Adelman (RSA), Advanced Encryption Standard (AES), and Data Encryption Standard (DES) were implemented and simulated in the Java programming environment in this study. Some selected text data files were used to drive the simulation. Metrics such as encryption time, decryption time, memory utilization and data size were used to measure the performances of the selected algorithms. When the three selected algorithms were run on 50 bytes data size, AES had encryption time of 40ms, decryption time 37ms, and memory utilization of 12MB. DES had encryption time 38ms, decryption time of 35ms and memory utilization of 08MB. RSA had encryption time 36ms, decryption time of 34ms and memory utilization of 10MB. When the three selected algorithms were run on 500 bytes data size, AES had encryption time of 65ms, decryption time 61ms, and memory utilization of 25MB. DES had an encryption time of 60ms, decryption time of 58ms and memory utilization of 17MB. RSA had an encryption time of 69ms, decryption time of 65ms and memory utilization of 21MB. In conclusion, DES performed better than other algorithms in both small and large data sizes for all metrics considered.
Analisis Prediksi Data Kasus Covid-19 di Provinsi Lampung Menggunakan Recurrent Neural Network (RNN)

This study aims to examine the architectural performance of the Recurrent Neural Network (RNN) model in predicting Covid-19 cases in Lampung Province. The RNN method is part of Deep Learning which will be used to model data on Covid-19 cases in Lampung Province from March 26, 2020 to March 28, 2021. The RNN model was chosen because the Covid-19 data is in the form of a time series and the advantages of RNN are that it can capture information on the data time series using multiple network layers which allow better modeling and resulting in high prediction accuracy. The data is divided into 3, namely active cases, recovered cases, and dead cases. After preparing the data, the 368 data were divided into 294 initial latih data and 74 test data. After latih on the data for each data, then a test is carried out on the data for each data as a reference for predicting the latest data. The most optimal results show the cumulative active case model with RMSE=0.0022; for cumulative recovery cases obtained RMSE = 0.0007; while the cumulative death cases obtained RMSE = 0.0012. Based on the modeling error, then make predictions on the three cases which results in RMSE = 0.001 for cumulative active cases; RMSE=0.0027 for cumulative recovery cases; and RMSE=0.001 for cumulative death cases.
FNAB and Anatomic Pathology Biopsy Accuracy in Thyroid Nodule Diagnosis

Background: The problem examined in this study is the accuracy of the FNAB examination compared to the gold standard histopathology.Objective: To determine the value of sensitivity, specificity, positive and negative predictive values , and the accuracy of the FNABMethod: This study uses a retrospective method. The population was patients with thyroid nodules in Pare Regional Hospital, Kediri, in 2015-2019. The sampling technique is Simple Random Sampling Probability. The sample was the patients who had been diagnosed with thyroid nodules and underwent FNAB examination followed by histopathology biopsy. The instrument used was secondary data collection inpatient medical record data. The data can be processed through diagnostic tests.Results: FNAB sensitivity value of 66.6%, a specificity value of 97%, a positive predictive value of 90.9%, and a negative predictive value of 86.8%, and an accuracy rate of 87.7%Conclusion: FNAB can be used as a first-line examination in diagnosing thyroid nodules but cannot replace histopathological examination as a gold standard.
Cancelling, Counter-speech and Censorship

Since the post-2016 period, the role of social media as a public utility and a platform for expression has drawn increased attention, debate, and - for some - ultimately concern. This has become especially true regarding its role in both facilitating and yet also restricting expression in online communities. While social media has been oft turned towards as a vehicle for social action, this paper raises simultaneous concerns still developing regarding its use for doing so. Ultimately, social media, while a viable tool for social change, also presents distinct and developing concerns for our civil liberties particullarly in an age dominated by online algorithms, private regulation of expression, and an increasingly virulent era of 'cancel culture'.
PENGARUH BLENDED LEARNING BERBANTU GOOGLE CLASSROOM TERHADAP HASIL BELAJAR PADA MATERI VIRUS

&#x0D; This study aims to determine the effect of the use of Google Classroom-assisted Blended Learning on student learning outcomes on viral material at SMAN 4 Luwu. This research is a quasi-experimental study with a nonequivalent control group design. The population in this study amounted to 186 students. The sample of this research is class X MIPA 5 and X MIPA 6 each totaling 31 students who were selected by purposive sampling. The data collection technique was carried out by learning outcomes tests. Data analysis used descriptive and inferential statistical analysis, namely normality test, homogeneous test and independent sample t test. The results of the descriptive test obtained the average value in the experimental class which was 84.68 while in the control class the average value obtained was 81.81. The results of the analysis of hypothesis testing are 0.043 &lt;0.05, it is concluded that there is an effect of using the Google Classroom-assisted Blended Learning learning model on student learning outcomes in class X virus material at SMAN 4 Luwu.&#x0D; &#x0D;
A survey of payment challenges in fraud detection in digital transactions methodologies

Any theft of the real card (Credit) or the arrangement of the card data, or potentially cardholder data, is the start of a Visa fraud. A vendor store agent duplicating deal receipts is one example of a tradeoff that can occur in a variety of ways. Because of the wide geographic reach that security lapses on databases holding MasterCard data might have, security lapses on databases including MasterCard data can be particularly large and costly. In one example in 2005, 40 million Visa customer accounts were stolen as a result of a single trade off of a massive database including charge card information. This had global consequences since fresh cards had to be issued to a huge number of cardholders all over the world. There are mays of credit card fraud, in this paper I concentrate some of them. Now a days we are facing a risk in payment of card, everyday payment for the exchange has been increasing as a result of the rising technique of instalment type and the introduction of new channels for the exchange.
Optimal Intermittent Particle Filter

The problem of the optimal allocation (in the expected mean square error sense) of a measurement budget for particle filtering is addressed. We propose three different optimal intermittent filters, whose optimality criteria depend on the information available at the time of decision making. For the first, the stochastic program filter, the measurement times are given by a policy that determines whether a measurement should be taken based on the measurements already acquired. The second, called the offline filter, determines all measurement times at once by solving a combinatorial optimization program before any measurement acquisition. For the third one, which we call online filter, each time a new measurement is received, the next measurement time is recomputed to take all the information that is then available into account. We prove that in terms of expected mean square error, the stochastic program filter outperforms the online filter, which itself outperforms the offline filter. However, these filters are generally intractable. For this reason, the filter estimate is approximated by a particle filter. Moreover, the mean square error is approximated using a Monte-Carlo approach, and different optimization algorithms are compared to approximately solve the combinatorial programs (a random trial algorithm, greedy forward and backward algorithms, a simulated annealing algorithm, and a genetic algorithm). Finally, the performance of the proposed methods is illustrated on two examples: a tumor motion model and a common benchmark for particle filtering.
Development of BSM Interactive Multimedia Based on Construct 2 as an English Language Learning Media for Grade 3

This study aims to develop learning media in the form of an Android-based English educational game. For the presentation of the material using English subjects for class 3 MI, such as names of vegetables, fruits, animals, and colors. The development of learning media uses software construct 2 as an application for making English educational games. Learning media testing was carried out by 13 students of class 3 MI Mamba'ul Ma'arif. Data was collected by distributing test result questionnaires and response questionnaires. The research method used is the ADDIE method, by applying several stages, namely the first Analysis (analysis), the second Design (design), the third Development (development), the fourth Implementation (implementation), and the fifth Evaluation (evaluation).&#x0D; The results of the feasibility test of the material expert learning media show that it is very feasible by obtaining a value of 4.5. Media experts show it is very feasible with a score of 4.3. And the results of student trials obtained an average test score of 80.7, test 2 of 83.4, and test 3 of 91.1. Based on these results, it can be concluded that the learning media in the form of educational games is very interesting and suitable to be used to help students learn grade 3 MI.
PENINGKATAN HASIL BELAJAR BIOLOGI KELAS IX SMP ITTIHAD MAKASSAR MELALUI MODEL PEMBELAJARAN QUANTUM TEACHING DENGAN METODE PRAKTIKUM

The study aims was to improve the biology learning outcomes of Class IX students of SMP Ittihad Makassar through the application of the Quantum Teaching model to Class IX students of SMP Ittihad Makassar with the practical method. This type of research is classroom action research with data collection techniques through tests and observations. Observational data were analyzed qualitatively in the form of a description of student learning activities, and then analyzed quantitatively in the form of averages and categorization of student learning outcomes. The subjects in this study were all 20 students of class IX SMP Ittihad Makassar. The results of this study indicate an increase in biology learning outcomes for class IX students of SMP Ittihad Makassar through the application of the Quantum Teaching model with the practicum method. This can be seen from the results of student learning tests which show an increase from cycle I to cycle II with an average of 63.00% increasing to 82.00%.
Error analysis of descriptive writings by pre-service EFL teachers: A case study in Indonesia

This research investigates pre-service EFL teachers’ writing proficiency by analyzing errors made in their descriptive essays. Conducted in one teacher training university in Indonesia, 40 randomly selected writing products assigned for the Writing course of 160 pre-service teachers, who are novice writers, were qualitatively analyzed. The result of the analysis showed that there were sentence fragments with 21 times or 42 %. It means that sentence fragment was the most dominant error done by students. Sentence fragment appeared due to the absence required in a complete sentence. Run-on sentence and comma splice existed 16 times or 32 %. Run-on sentences and comma splices appeared due to the wrong in combining two independent clauses. Choppy sentence were found 10 times or 20 % due to the use of too many short sentences, sometimes often repeating the same word at the beginning of a sentence. Stringy sentence were identified 3 times or 6 % of the whole essays due to the use of too many clauses with connected words. These clauses strung together forming one very long ineffective sentences. The findings are expected to reveal a comprehensive evaluation of writing proficiency of pre-service teachers and call for students, teacher educators, and policy makers to more concern with this crucial issue.
MODEL OF PROJECT-BASED AND COGNITIVE COMPETENCIES-INFUSED LEARNING IN THE GRAMMAR CLASS OF ELESP

Model of learning is a guideline that teachers will use to let their teaching more comprehensive and practical to facilitate the achievement of the learning goal. A dynamic approach suited to teaching in which students explore real-world problems and challenges, simultaneously developing 21st-century skills while working in small collaborative groups is Project-Based Learning. The purpose of the study is to analyze the used model of Project-Based and Cognitive competencies-infused learning in the grammar class of English Language Education Study Program. This study employed a qualitative design where the data are the components of the existing models of learning in grammar classes of English Language Education Study Program. Besides, online class observation and grammar class syllabus documents are used as instruments. The findings of analysis revealed that Methods that generally used in the online class observation are Computer-Assisted Instruction (CAI), Scaffolding, Reciprocal method, Cooperative Learning while mostly used Lecturing, General Discussion, and Presentation to delivering material. The indicator that could be seen in syllabus document and class observations was Critical Thinking from Cognitive competences indicators. The Project-Based Learning indicators could also be seen directly from syllabus documents and online class observations. Intellectual Challenge and Accomplishment was mostly dominated seen in the model.
Modern requirements for teachers of foreign languages to improve professional skills and personal qualities

The article describes the modern requirements of a foreign language teacher to improve professional skills and personal qualities. About how a modern teacher should know his subject at a high professional level and should possess modern technical means of teaching. The article also talks about methods of teaching the students to foreign languages at a high level.
The Impact of Innovation and Environmental Turbulence on Financial Performance

Present research seeks to develop a conceptual model for exploring the impact of innovation on financial performance.In addition to that, the current study has suggested environmental turbulence as a moderator for the relationship mentioned above.The innovation literature and contingency theory supply starting points for developing the conceptual framework.Present research investigates the impact of innovation and environmental turbulence on financial performance.The paper has some preliminary findings since it is suitable for management to direct their effort and time in interpreting the impact of innovation on financial performance.Moreover, the conceptual model delivers insights for considering the effect of environmental turbulence as a moderator variable on financial performance.
Research on Modeling and Simulation System of Economic Factors Based on Swarm Platform

Based on the VAR model, this paper uses the stepwise regression analysis method to analyze the main influencing factors of the economy, and empirically analyzes the impact of Nanning's fixed asset investment on urban and rural economic development in the past ten years. Use eviews statistical analysis software to perform regression analysis on the data to obtain a regression model, and build a VAR model according to investment and income, and finally find out the correlation of variables. On the basis of the existing theory (genetic algorithm, cellular automata and classification system), according to the agent-based modeling and simulation method Swarm, according to the steps of agent-based distributed simulation of complex system, modeling and simulation are carried out. The abstraction level of simulation is established on the big data computing level, and the final simulation results are briefly explained and explained.
Review on facial expression modeling

Facial modeling has been an ongoing research for many years and still shows research trend due to its relevance to current technology. Many applications incorporate facial expression modeling with the help of facial tracking, facial animation and facial recognition. The existing performance of the modeling method faces the challenges to perform well due to many factors. Currently, the use of 2D images and videos as inputs for modeling process are gaining popularity. However, current technologies and development had extended the trends towards acquiring 3D human data. This paper provides an overview on variety of modeling techniques based on human facial model that can lead to future research.
Live Forensic to Identify the Digital Evidence on the Desktop-based WhatsApp

The live forensics method was used to acquire lawful digital evidence data from device memory in the WhatsApp application, particularly for desktop-based WhatsApp. There has been little research on live forensics on desktop-based WhatsApp applications. These studies involve mimicking crime cases in cyberspace using the Instant Messenger application. Much of the acquisition process is completed only once, even though many possible conditions may arise during the purchase process. Investigators or experts can employ digital evidence data discovery to identify crimes that have occurred. The stages of research carried out in detecting digital evidence are data collecting, the examination process, and the acquisition of analysis and reporting outcomes. During the data-gathering phase, a case simulation dataset was obtained. The examination process stage results in the integrity of the duplicated data; data reduction is performed on data related to fundamental operating system components, influential application features, and incomplete data. According to the investigation findings, there are difficulties in looking for digital evidence, and the features of each digital evidence vary. The simulation file contained many reports on the finds of digital evidence. As a data acquisition method, the characteristics of live forensics are limited to the data retrieval process in RAM. Based on these findings, it is possible to conclude that the data collection and examination processing were completed effectively. The analysis results were acquired, and the report was presented with the indicated digital evidence. Further study can be paired with chip-off procedures on RAM devices for data recovery.
Applications of Social Attribution Theory in XAI

A major problem facing artificial intelligence ethics is how to give AI the status of the agent and gain the trust of human beings. This is accompanied by the rise of Explanatory AI (XAI). The social attribution theory (SAT) started from the perception experiment of Hyde and others, then psychologists conducted a long-term analysis of the causes and reasons of human intentional action, and Mahler built a complete social psychological attribution model from this. Because SAT is based on action analysis, it can reflect its vast application potential in XAI, including the interpretation of artificial agent action, interpretation of beliefs and other folk psychology concepts, analysis of group intelligence, and the construction of normative agent action and the corresponding ethical explanation. These explorations can provide new ideas for XAI.