Reviewerly/exHarmony huggingface dataset:
THE RELATIONSHIP BETWEEN STUDENTS’ LEVEL OF POSITIVE THINKING AND THEIR ENGLISH SPEAKING ANXIETY

Every student wanted to speak in English without feeling anxious, many of them really suffered from anxiety. Students who have negative thoughts while they are speaking in English, caused the negative result. Meanwhile, students who have positive thinking while they are speaking in English, will have positive result. The present study employed a quantitative approach, wherein a questionnaire was administered to a sample of 67 second-semester students enrolled in the English Education program at the University of Muhammadiyah Prof. Dr. HAMKA. The sample was collected with the use of the purposive sampling method. The result shows that the data calculated were rvalue= 0.315, rvalue ≥ N.Sig 5% (0.315 ≥ 0.01), and it was rvalue ≥ rtable (0.315 ≥ 0.240) and tvalue ≥ ttable (2.673 ≥ 1.996). As a result, the null hypothesis (Ho) was rejected and the alternative hypothesis (Hi) was accepted. So, it told that there was a negative correlation between students’ level of positive thinking and their English speaking anxiety, and it was 0.315 in the low category.
The Effect of Academic Motivation on RPL Program Students’ English Proficiency Test Score

The need for education is increasing and getting more complex along the time for it is a crucial need to prepare better human resources. Currently, higher education is attended by adult learners who are not only study but also work in the industry since the competition in the workplace is getting harder in this globalization era which implicitly requires English proficiency of the workers. Those who work while study must have a motivation either intrinsic or extrinsic to pursue higher education. Thus, this study aims to investigate the effect of academic motivation on RPL program students’ English proficiency test score. This study employed a descriptive quantitative method involving 27 RPL program students majoring in Pharmacy. Data obtained from the Academic Motivation Scale and students’ TOEIC scores were analyzed quantitatively using simple linear regression technique with the help of SPSS 22.0. This study found that even though the data were normal and linear, academic motivation had no effect on the students’ English proficiency test scores. This might happen because there are way more complex factors that influence academic achievement or academic performance in the results of English proficiency test.
Healthcare Information Systems Security Maturity Assessment

In the era of technology and an increasingly interconnected environment, information security has become ever more important and challenging. With the expansion in technology adoption, integration, and dependency, the vulnerability of healthcare organizations to cyber threats is a serious issue. Information security is necessary for organizations to protect their valuable and sensitive data from both internal and external threats. Organizations are contending with technological threats to the productivity, profitability, and safety of their employees and customers at a historically unprecedented rate, and the healthcare industry faces some of the greatest potential consequences. These threats challenge the viability of these organizations, and the financial risks both in remediation plans and penalties continue to raise the stakes. Healthcare organizations must address these threats with technology advancements, strategic project management, and decisive leadership.
Classification of Real and Deepfakes Visual Samples with Pre-trained Deep Learning Models

Serious security and privacy problems have arisen as a result of significant advancements in the creation of deepfakes. Attackers can easily replace a person’s face with the target person’s face in an image using sophisticated Deep learning (DL) algorithms to spoof their identity. Deepfakes detection algorithms have been proposed in response to the growing concerns about the potential harm caused by deepfakes. However, a reliable deepfakes detector that can keep up with contemporary deepfakes creation techniques is required. In this work, we have proposed an end-to-end methodology for detecting manipulated visual content. We used multiple CNN models i.e., ResNet18, ResNet50, DenseNet65, DenseNet77, and DenseNet100 along with the SVM classifier to compute effective cues from the input facial faces to distinguish between actual and altered content. We have also applied the concept of transfer learning to solve the issue of model over-fitting and improve generalizability against different manipulation algorithms. A comparison study is carried out to evaluate the performance of several feature extractors. Through thorough experiments performed using the Deepfakes Detection Challenge dataset, our results demonstrated that DenseNet100 surpasses the other CNN models by better recognizing deepfakes.
Improving Data Security in Cloud Computing

The objective of this project is to create a secure method of encrypting and storing data in cloud computing settings. In order to accomplish this, we compare the performance of three popular encryption algorithms—AES, DES, and MES—with various key lengths. Finding the ideal encryption technique and key length for our project is the goal of this evaluation. A secure system for encrypting and storing data in cloud computing settings is the anticipated result of this project, and it can help safeguard sensitive data from unwanted access and potential security breaches.This study can help with the future development of more effective cloud security solutions by illuminating the efficacy of various encryption approaches in protecting data in the cloud.
Row mixture-based clustering with covariates for ordinal responses

Abstract Existing methods can perform likelihood-based clustering on a multivariate data matrix of ordinal data, using finite mixtures to cluster the rows (observations) of the matrix. These models can incorporate the main effects of individual rows and columns, as well as cluster effects, to model the matrix of responses. However, many real-world applications also include available covariates, which provide insights into the main characteristics of the clusters and determine clustering structures based on both the individuals’ similar patterns of responses and the effects of the covariates on the individuals' responses. In our research we have extended the mixture-based models to include covariates and test what effect this has on the resulting clustering structures. We focus on clustering the rows of the data matrix, using the proportional odds cumulative logit model for ordinal data. We fit the models using the Expectation-Maximization algorithm and assess performance using a simulation study. We also illustrate an application of the models to the well-known arthritis clinical trial data set.
E-mail Spam Detection and Phishing link Detection Using Machine Learning

Phishing, which tricks individuals into revealing delicatedata like login credentials and financial details, is the most widespread type of cybercrime. Attackers typically use electronic mail, prompt messaging, and telephone calls to initiate these attacks. Despite ongoing efforts to prevent phishing attacks, current measures are not entirely effective, as the amount of phishing emails has enlarged significantly in current years. While numerous methods have been developed to filter out phishing emails, there is still a need for a comprehensive solution. This survey is the first of its kind to examine the use of N-L-P and ML methods for identifying phishing electronic mail. The analyzesof state_of_the_art N- L-P approaches that are presently being used to detect phishing electronic mail at different periods of the outbreak, with a focus on M-L methods. These methods are compared and evaluated in-depth.
The Use of Snakes and Ladders Game to Improve Students’ Grammar at the Second Grade of Mts DDi Baru

The second graders of MTs DDI Baru face several issues in learning English. Those become obstacles for them to get good achievement in the subject. One of the most difficult issue for them is they could not even compose a simple sentence properly using basic tenses such as simple present and simple past tense. The researcher tried to use game-based learning, in this case, using Snakes and Ladders game to solve the problem. So that, this research aims to find out the significant effect of using of snakes and ladders game in improving students’ grammar ability. This research design applied research with one pre-test and one post-test design in the experimental and control class. From 5 classes, the researcher chose 2 classes as sample by using cluster random sampling. The data analysis result revealed that the post-test mean score (74.07) is greater than the pre-test mean score (37.24) in experimental class. The results of the t-test also confirm that the p-value is 0.001, or smaller than 0.05, whereas the t-value is 8.87 or greater than t-table 2.048. So, by considering the p and the t value, the reseacher withdraw conclusion that H₁ is accepted which states that the use of the Snakes and Ladders game can improve students’ grammar. However, another interesting finding reveals that there is also improvement of students’ scores in the control class but not as significant as in the experimental class. The mean score increased 15.86 points while in the experimental class it increased 36.83 points
Transformation of the university teachers’ professional competencies structure in the aspect of the modern era requirements

The article considers the problem that determines the main competencies of the university teachers’ professional activity and the content of these competencies. The content of the university educational activity is directly connected with the teacher’s professionalism. The task of the university is to form a competent teaching staff, which provides for a high level of training of specialists graduated from the university. Currently, the education system is undergoing changes caused by the growth of society technological development, which affects the content of teacher’s professional competencies. The purpose of this article is to specify the competencies that characterize the professional activity of a modern teacher. The author has identified the key professional competencies of a university teacher, analyzed and presented the generalization the competencies content. The results of the work can be useful for teachers of higher education to determine the direction of professional development, and to design the trajectory of professional selfdevelopment.
Imagining permanence on the web: Tracing the meanings of long-term preservation among the subjects of web archives

This article explores how web archiving impacts the online communication practices of individuals whose personal websites have been archived by major public libraries. Drawing on interviews with website creators and analysis of their written reflections on the archiving process, it demonstrates how web archiving alters the meanings people attach to their online activity. In most cases, the preservation of their website in a national web archive sees individuals perceive their communication practices as having wider cultural and historical significance. These meanings are shaped by the distinctive interaction between archiving and archived actors and propelled by imaginaries surrounding the culture and history of the collecting institution. Based on these findings, this article argues that web archiving can be productively understood as an intervention in the dynamics of online sociality and calls for reflexive archival and research practices that attend to the short- and long-term impacts of altering the visibility of online material.
Encrochat: The hacker with a warrant and fair trials?

This paper introduces the Encrochat operation as an example of the technological, cross-border, and cross-disciplinary complexity of one contemporary digital investigation. The use of encryption for large-scale criminal activity and organized crime requires law enforcement to act pro-actively to secure evidence, to rely on cross-border evidence exchange, and to use more efficient digital forensic techniques for decryption, data acquisition, and analysis of volumized evidence. The Encrochat investigation also poses the question whether the traditional fair trial principle can still ensure minimum state intrusion and upholding of legitimacy in the new ubiquitous investigation process, where digital forensics methods and tools for hacking and data acquisition are used to identify and arrest thousands of suspects and collect evidence in real-time during criminal activity. The operation is examined through the lens of the right to a fair trial, as codified in Art. 6 ECHR, in order to exemplify three challenging aspects. Firstly, in cross-border investigations there are no binding digital forensics standards in criminal proceedings or forensic reports exchange policy which demands reliability and compliance with Art. 6 ECHR-based evidence rules. Secondly, the defense's stand is not sufficiently addressed in current digital evidence legislation or mutual trust-based instruments at the EU level. Finally, the judicial process lacks scalable procedures to scrutinize digital evidence processing and reliability and is exposed to technology dependences. The identified gaps and their practical impact require a novel approach to digital evidence governance.
English Thematic Meaning Exploring Class under the New English Curriculum

The New English Curriculum(2017 edition, 2020 revision) advocated that English teachers should pay attention to meaning of the theme in teaching and formulate overall goals of teaching units pointing to the development of core competences of English. The author discussed the connotation and importance of thematic meaning exploration in English classroom to students' English learning, and explored the implementation situation and paths in China.
The Metaverse’s Thirtieth Anniversary: From a Science-Fictional Concept to the “Connect Wallet” Prompt

Abstract The metaverse is equivocal. It is a science-fictional concept from the past; it is the present’s rough implementations; and it is the Promised Cyberland, expected to manifest some time in the future. The metaverse first emerged as a techno-capitalist network in a 1992 science fiction novel by Neal Stephenson. Our article thus marks the metaverse’s thirtieth anniversary. We revisit Stephenson’s original concept plus three sophisticated antecedents from 1972 to 1984: Jean Baudrillard’s simulation, Sherry Turkle’s networked identities, and Jacques Lacan’s schema of suggestible consumers hooked up to a Matrix-like capitalist network. We gauge the relevance of these three antecedents following Meta’s recent promise to deliver a metaverse for the mainstream and the emergence of blockchain-oriented metaverse projects. We examine empirical data from 2021 and 2022, sourced from journalistic and social media (BuzzSumo, Google Trends, Reddit, and Twitter) as well as the United States Patent and Trademark Office. This latest chapter of the metaverse’s convoluted history reveals a focus not on virtual reality goggles but rather on techno-capitalist notions like digital wallets, crypto-assets, and targeted advertisements. The metaverse’s wallet-holders collect status symbols like limited-edition profile pictures, fashion items for avatars, tradable pets and companions, and real estate. Motivated by the metaverse’s sophisticated antecedents and our empirical findings, we propose a subtle conceptual re-orientation that respects the metaverse’s equivocal nature and rejects sanitised solutionism. Do not let the phantasmagorical goggles distract you too much: Big Meta is watching you, and it expects you to become a wallet-holder. Blockchain proponents want this as well.
Pengembangan Media Pembelajaran Kartu Cerdas sebagai Penguatan Keterampilan Membaca Siswa Kelas Rendah di Sekolah Dasar

This researcher aims to develop Smart Card learning media which is motivated by the lack of utilization of the media used by educators until causing monotony and lack of student response in learning so that it has an impact on reading skills. The use of media in learning can help foster student focus. Smart Cards are cards that contain writing and pictures, so students can easily digest the writing with the help of pictures. This research is a development research that refers to the developer model Borg and Gallaccording to the developer which uses seven stages in the research namely Research and Information Collection, Planning, Develop Preliminary Form of Product, Preliminary Field Testing, Operational Product Revision, Main Field Testing, Operational Field Testing. Based on the research results, validation results of media experts obtained score data of 92% with the criteria of "Very Eligible", from linguists with a score of 87% with the criteria "Very Eligible", from material experts with a score of 91% with the criteria of "Very Eligible", as well as the results of large-scale field trials with the value of the questionnaire filled in by students obtaining 95% with the criteria of "Very Practical". The questionnaire filled out by the teacher or colleagues obtained 97% with the criteria "Very Practical". Fill in the observation sheet questionnaire to get 100% with the criteria "Very Practical”. Questionnaire observation sheets of students' reading skills obtained 65% having achieved a classical completeness standard of 65%.
Design and implementation of low power Advanced Encryption Standard cryptocore utilizing dynamic pipelined asynchronous model

The Advanced Encryption Standard (AES) has added new dimension to cryptography with its potentials of safeguarding the health care devices and systems. This paper presents the design of low power VLSI architecture for AES crypto application focusing on ECG signal transmission. The proposed design addresses the next generation cyber physical security requirement and low power for portable biomedical digital assistant devices. The proposed work utilizes on-chip built-in BRAM, configurable pipelining stages for combinational path, clock gating mechanism, and dynamic pipelined asynchronous operation. The use of dynamic pipelined asynchronous model (DPAM) controls different functional units of AES in controlled sequential order with gating of global clock and reset signals. This prevents unwanted switching activity in the functional units that waits for valid data. The performance of the proposed low power DPAM-AES architecture is compared with existing low power architectures in terms of power consumption, area, delay and throughput. The proposed DPAM-AES architecture results in power consumption starting from 260 mW to 329 mW, which are 47 mW to 385 mW lesser power for the frequencies of 100 MHZ to 800 MHZ respectively. The low power AES micro architecture is designed using VHDL and simulated, synthesized and implemented using Vivado design suite targeting ZynqSoC 7z020clg484-1 FPGA platform. The performance of the proposed AES micro architecture can be further improved by targeting to ASIC implementation of the designed AES core.
In good times and bad: Low-cost mobile teaching during a pandemic

In view of school closures due to the COVID-19 pandemic, this paper examines how a Home-Based Learning program affects learning outcomes of children in under-resourced communities. To overcome limited internet connectivity, the program provides remote instructions via phone calls and simple text messages along with automated voice calls to engage children enrolled in grades one to five in activity-based learning content. This intervention was conducted in three districts in the state of Odisha in India. Using a difference-in-differences framework, we find that the intervention led to a statistically significant improvement in basic number recognition and arithmetic operations, and language learning scores of children by 4.69 percentage points and 5.52 percentage points, respectively. Our results are robust to alternative methods of estimation and application of Lee bounds, thus indicating that well-designed low cost interventions could be a useful supplement for continued learning in the face of sudden shocks in low income countries. With a rise in hybrid format of teaching and learning, such interventions have the capability to cushion the decline in learning levels and provide a safety net in the event of school closures.
SCHOOL IN USE AND DEVELOPMENT OF ICT-BASED LEARNING MEDIA AT PLUMBANGAN 01 STATE ELEMENTARY SCHOOL

The results of the analysis of the 8 SNP standards contained in the School Self Evaluation (EDS) UPT SD Negeri Plummbang 01 researchers found weaknesses in process standards, especially teacher competence, which still needed to be improved in the process of using ICT-based learning media and development. The type of this research is school action research. This research was conducted at Plukangan 01 Public Elementary School in November 2021 with the research subjects being all teachers of Resapombo Public Elementary School. The technique of collecting data from this school action research is through qualitative data obtained from observation/observations, interviews and document studies. This procedure includes the following stages: (1) planning, (2) implementation, (3) observation, and (4) reflection. Based on the results of reflection, monitoring and evaluation that have been carried out, it can be concluded that cycle 1 and cycle 2 activities have increased so that all objectives of the school action research activities are declared successful. Teacher competence in using ICT-based learning media and development is said to have increased.
Using FinBERT as a refined approach to measuring impression management in corporate reports during a crisis

This paper presents the findings of sentiment analysis as a refined approach to detecting impression management that may be present in the Chairman’s Statements of companies during an exogenous event such as the Corona virus pandemic. FinBERT, a more advanced machine learning model of natural language processing (NLP), was used to investigate the change in net sentiment expressed in the Chairman’s Statements of a sample of South African JSE-listed companies before and during the pandemic. A computation of net sentiment for each report was performed. Overall, no generic pattern of communication in the Chairman’s Statements emerged between the periods researched. Impression management tactics may vest within reports on an entity-specific basis and may be the exception, not the rule. Considering the increasing amount of unaudited narrative disclosure presented in formal corporate communication, consideration must be given to whether the sentiment expressed in these formal corporate reports is balanced, clear and transparent. Content analysis has historically been labour-intensive. More accurate ways of analysing growing bodies of financial text would be relevant to investors, analysts, key stakeholders, policy makers and academics. Pre-trained NLP models such as FinBERT offer a specialised way of understanding the sentiment of financial text. Research exploring impression management in corporate narrative sections using FinBERT is still gaining momentum across the world and is limited in South Africa. To the researchers’ knowledge, this is one of the first South African studies to employ FinBERT as an innovative, accurate and efficient approach to analysing the sentiment in the Chairman’s Statement.