Reviewerly/exHarmony huggingface dataset:
The Effect of Mind Mapping Strategy Towards Students Writing Skill at the Tenth Grade Students of MA Anwarul Hidayah Ciputri Menes Pandeglang in Academic Year 2022/2023

This study aims to investigate the implementation of Mind Mapping strategy towards student's writing descriptive at the tenth-grade students of MA Anwarul Hidayah Menes Pandeglang. The study used quantitative approach, while the method used is quasi experimental method with pre-test and post-test design. It used a triangulation of data collection methods involving pre-test, treatment and post-test. The data obtained from 2 classes, they are experiment and control class. The experimental class for this research was XA and the control class was XB. Each class consists of 30 students. The total sample is 60 students. The experimental class’s mean score on the pre-test was 50.23, while the control class’s mean score on the pre-test was 48.57. On the other hand, the post-test result is, the mean score of experimental class was 69.07, while the mean score of control class was 63.33. The hypothesis calculating was done by using SPSS 22. The result obtained from hypothesis test is 0.00 &lt; 0.05 it means that there is significant effect of Mind Mapping strategy towards student's writing descriptive at the tenth-grade students of MA Anwarul Hidayah Ciputri Menes Pandeglang in academic year 2022/2023.
COLLABORATIVE WRITING ON GOOGLE DOCS: PERCEPTION OF ELEVENTH GRADE STUDENTS’ DESCRIPTIVE PARAGRAPH IN PGRI VOCATIONAL HIGH SCHOOL 1 PALEMBANG

The researcher's experience when conducting field experience practice (PPL) at PGRI Vocational High School 1 Palembang served as inspiration for this research. The researcher found that students experience problems when they want to write, including due to a lack of practice, a weakness in using correct grammar, and a lack of motivation. Therefore, in this study, the researcher used a collaborative learning method using Google Docs. The aimed of this research is to implement the use of Google Docs with grade XI students in collaborative writing of descriptive paragraphs and to determine students' perceptions of the use of Google Docs in collaborative writing of descriptive paragraphs. This research used the descriptive-qualitative method with a sample of 32 students. Data were collected through observation, questionnaires, and documentation. Looking at the results of students' implementation of the use of Google Docs in collaborative writing of descriptive paragraphs, it is said to be successful because students are able to exceed the KKM score of 75. For students' perceptions, it can be said to be a positive perception because most of them strongly agreed and agreed on the 20 questionnaire statements that researchers distributed; this means that students were able to write the text better.
EFL TEACHERS’ ATTITUDES AND EXPERIENCES ON THE IMPLEMENTATION OF MULTILITERACIES

The main problem in this research is: what are the elements that influence the attitudes and experiences of EFL teachers in implementing multiliteracy, and how can EFL teachers be used as role models for implementing multiliteracy in terms of their attitudes and experiences? The purpose of this research is to find out how the attitudes and experiences of teachers towards students during the learning process affect them and how multiliteracy can be applied during the teaching and learning process, whether it makes learning effective or vice versa. This research was carried out at SMP PGRI 1 of Palembang. This research was carried out using qualitative methods. First, the researcher made observations at school to find out how effective the teaching and learning process was in class, especially in English lessons. Furthermore, the researchers conducted interviews with the English teacher and distributed 20 questionnaires to 30 students in class VIII.4 in the even-numbered 2022/2023 academic year. Based on the findings from this study, the researcher concludes the results of the research analysis. And from the results of this analysis, the researchers concluded that 90% of SMP PGRI students liked English lessons and always got good motivation and role models from the teacher, meaning that the teacher could provide good motivation to students and always give a good attitude during the learning process. Students are also more active in the application of multiliteracy because there is good interaction between the teacher and students.
CLASSROOM INTERACTION IN COMMUNICATIVE LANGUAGE TEACHING OF SECONDARY SCHOOL

This research aimed to describe the dynamics of classroom interaction and examine the factors influencing it. The researcher utilized qualitative methods, including classroom observation, semi-structured interviews, and questionnaires. The findings revealed that the teacher predominantly led and controlled the interaction. Good interaction only occurs at the beginning of the lesson, so for the most part, the teacher initiates and the students only responded to the teacher by giving answers in the form of phrases or words. For interaction between students they are interacted with their friends most of the time. But, mostly, it was not related to the English topic discussed. The researcher also found several factors affecting classroom interaction, such as students' lack of motivation, hesitancy to speak and engage in class discussions due to limited vocabulary, embarrassment, and fear of making mistakes.
Modified Arnold Transform and DNA Manipulation for Chaos-Based RGB Image Encryption

Multimedia applications use image encryption algorithms extensively to safeguard and authenticate digital images. This paper presents an RGB image encryption method, which uses Chaos, DNA, pixel sum, and modified Arnold transform. The suggested algorithm is validated to be robust and resistant to visual, statistical, differential, and brute-force attacks. Additionally, the resulting encrypted images pass all tests of the NIST SP 800-22 test suite.
Uncertainty Estimation for Complex Text Detection in Spanish

Text simplifcation refers to the transformation of a source text aiming to increase its readiblity and understandability for a specific target population. This task is an important step towards improving inclusivity of such target populations (i.e., low scholarity or visually/hearing impaired groups). The recent advancements in the field brought by Large Language Models improve the performance of machine based text simplification approaches. However, using Language Models to simplify large text segments can be resource demanding. A more simple model to classify whether the text segment is worth to simplify or not can improve resource efficiency, in order to avoid unnecessary text prompts to the Large Language Models. Furthermore, text simplicity categorization can also be used for other purposes, such as text complexity measurement. The discrimination of text segments into simple and complex categories might lead to a number of false positives or negatives for a not well-tuned model. A way to control the acceptance threshold, is the implementation of an uncertainty score for each prediction. In this work we explore two simple uncertainty estimation approaches for complex text identification: a Monte Carlo Dropout and an Deep Ensemble Based approach. We use an in-house dataset in the financial education domain for our tests. We calibrated the two implemented methods to find out which performs better, using a Jensen-Shannon based distance between the correct and incorrect outputs of the discriminator. Our tests showed an important advantage of the Monte Carlo Dropout over the Deep Ensemble Based method.
History of theoretical programming in Ukraine (contribution of Kateryna Yushchenko)

The scientific legacy of Kateryna Yushchenko, a distinguished Ukrainian scholar in the realm of theoretical programming is examined. This research underscores her individual contributions to the advancement of theoretical programming within Ukraine. The evolutionary stages of Kateryna Yushchenko’s pioneering work on the addressable language, recognized as the world’s inaugural “high-level” programming language, are meticulously explored. This investigation establishes that Kateryna Yushchenko initiated this groundbreaking study while affiliated with the Kyiv Institute of Mathematics under the Academy of Sciences of Ukraine. The antecedents that catalyzed the emergence of theoretical programming in Ukraine during the late 1940s and early 1950s are duly considered. This material illuminates the nascent phase of the scientist’s scholarly pursuits and her intellectual evolution against the backdrop of the contemporaneous development of information technology’s foundations. Scientist, having dedicated her entire life to the pursuit of information technologies, left a profound imprint on the training of programmers. Her contributions include the establishment of a series of instructional materials and the mentorship of numerous doctoral and aspiring candidates in the realm of mathematical sciences. This discourse underscores how the scientist’s dynamic involvement in both organizational and pedagogical spheres significantly contributed to the dissemination of cybernetics as a scientific discipline. Kateryna Yushchenko creative legacy served as a catalyst for the accelerated growth of theoretical programming within Ukraine and worldwide, effectively addressing pressing practical challenges during her lifetime and enduring as a valuable resource for contemporary research into theoretical programming quandaries.
Chua’s Circuit with Nonlinear Energy Storages and Its Synchronization

The paper deals with the development of a theoretical framework to study and control electrical devices with saturated magnetic circuit. We use the interval methods to replace the nonlinear function with its piecewise linear boundaries. These boundaries allow us to define the domain in the state space where all system motions are defined. One can use the above-mentioned domain to reduce the area of study system possible motions and design a closed-loop control system to form desired motions of system state variables. We show the main points of our approach by considering Chua’s circuit, which is modified by using a coil with a ferromagnetic core as well as using controllable voltage sources. We use voltage sources to control any of Chua’s circuit state variables easily. Our studies show that the use of an unideal coil changes the circuit attractor. Moreover, changing the operation point of the coil gives us the possibility to form unsymmetrical attractors and chaotic oscillations. We think it is a way to improve the security features of the considered circuit. Another way is the use piecewise linear functions instead of the nonlinear ones. The small differences between nonlinear and piecewise linear functions form after a time the entirely different motion trajectory. Since there are several methods to define piecewise linear boundaries for nonlinear functions, one can define different functions and build different circuits based on Chua’s circuit with a ferromagnetic core coil. On another hand these different boundaries allow us to define a control signal to compensate for the circuit’s inner dynamic and perform its synchronization with an error of less than 0.1%.
Federated Learning for Collaborative Crop Disease Monitoring in Wheat Production

This study addresses the critical challenge of crop diseases in global agriculture by introducing a novel approach that combines wheat production, crop disease monitoring, and federated learning. Crop diseases pose a severe threat to food security, making early diagnosis and intervention imperative. Wheat, a staple crop with significant health implications, particularly concerning diabetes, requires comprehensive research and monitoring. Federated learning, a privacy-centric machine learning technique, emerges as a promising solution to this problem. It allows collaborative model training across decentralized data sources without exposing raw data, ensuring data privacy and security. The study's results, based on three models, demonstrate its effectiveness: Fast R-CNNs achieved an accuracy of 91%, recall of 93%, and F1-score of 87%; Mask R-CNNs reached an accuracy of 93%, recall of 95%, and F1-score of 88%; RetinaNet achieved an accuracy of 84%, recall of 89%, and F1-score of 74%. These results underscore the potential of this approach in revolutionizing disease detection and classification while contributing to global food security and sustainable agriculture. The future work involves refining the federated learning model, optimizing GATs integration, exploring advanced privacy-preserving strategies, and expanding applications to various crops and disease categories, promising a significant enhancement in the quality of life for individuals impacted by diabetes and further advancements in AIoT-driven agricultural disease monitoring on a global scale.
Advances, Challenges and Opportunities in Deep Learning Approach for Object Detection: A Review

Object detection is a major task in computer vision which have a widespread applications across various domains. Recognizing objects from sample images and videos is such a difficult task which literally utilized machine learning techniques. Prior studies have recorded outstanding performance in different object detection problem using deep learning approach. In this paper, we explores the advances in methodologies for object detection tasks, starting from traditional techniques to the recent surge in deep learning. It also discusses the diverse applications of object detection across domains such as healthcare, transportation, agriculture, retail, surveillance, and environmental monitoring. Furthermore, the paper highlights the opportunities and challenges associated with deep learning approach for object detection. Future direction of the limitation in the field such as class imbalance, unavailability of enough dataset, and interpretability were addressed. In conclusion, the paper provides a continuing scholarship in the area of object detection, serving as a valuable resource for researchers, in the field of machine learning and computer vision application for decision making.
Cybersecurity in ECE Curriculum, an Expanded Collaboration Program to Disseminate Real Security Experiences in Cyber-Physical Systems

Work in Progress: This paper presents the progress in an innovative practice in Cybersecurity Education. It is well-recognized that security is becoming more critical to protect modern infrastructure. Traditionally cybersecurity has been perceived as a skill mainly required in user applications or in the upper protocol layers. However, there are concerns about vulnerabilities in embedded systems or in the lower protocol layers. The range of skills needed must encompass an understanding of cyber-physical systems due to the potential impact on the operation of modern technologies. We report the results of a holistic intervention in an Electrical and Computer Engineering program. The changes go beyond simply adding a cybersecurity class; instead, we have multiple actions disseminated in several aspects of the academic program providing the students with a richer experience. Students learn about cybersecurity through several methods thanks to an ongoing partnership between the US ARMY DEVCOM at White Sands Missile Range (WSMR), and the Electrical and Computer Engineering Department at the University of Texas at El Paso (UTEP). The efforts include steering the academic programs and supporting the creation of a separate degree in Computer Engineering besides the existing Electrical Engineering program. Other interventions involve adding cybersecurity concepts in several courses required by all Electrical Engineering and Computer Engineering students. Other efforts include sponsorship of capstone projects and support for graduate teaching assistants specialized in promoting cybersecurity education to entire cohorts. Between fall 2018 and fall 2020, we had an informal collaboration between UTEP and the ARMY group. The formal partnership started in Spring 2021 and has continued through spring 2023. Each semester, at least one capstone project is specialized in designing and building cyber-trainer devices that the soldiers use in WSMR. The projects demonstrate relevant concepts to prepare students in a controlled portable environment. Since the fall semester of 2020, more than 200 senior students have incorporated cybersecurity awareness in their capstone project. In addition, there are six more courses where students get exposure to cybersecurity and an average participation of 60 students per semester. The last student cohort responded to a survey to understand the perceived gains in cybersecurity knowledge. Most students have a positive attitude toward the knowledge received and recognize the importance of the new skills. Some students went even further and decided to pursue careers in the area. Several students applied for internship experiences at the ARMY DEVCOM WSMR facility as part of the collaboration. We got additional funding to expand the traditional research projects and include graduate students.
Foundational Digital Forensics Skills and Learning: Exemplifying Social Justice

This full paper reports on the curricular design and IRB-approved participant feedback of a digital forensics workshop curriculum to either be a standalone learning or experience or integrated within a forensics component of a cyber security course (e.g. Network Perimeter Security). The workshop showcases skills needed for foundational digital forensics (DFR) fieldwork and explains pedagogical techniques and successful environments for building inclusive classrooms that have been successful as reported by heterogeneous students. Forensics topics in the curriculum are be selected from the following areas found in our foundational digital forensics course: data acquisition; processing crime/incident scenes; information retrieval from Windows, Macintosh, and Linux systems; recovering graphic, Word, Acrobat, and other file types; virtual machine forensics; investigating emails; examining social media data; writing investigation reports; studying the importance of ethics for expert witnesses; and, understanding expert testimony in digital investigations. The anticipated skills learned from the workshop are components of a full semester course which covers the basics for cybercrime and cyber-incidents to prepare students for interaction with law enforcement agencies, interaction with organizational forensic teams, and further digital forensic courses (e.g. Advanced Digital Forensics, Mobile Device Forensics, Incident Response, Malware Analysis, and Management of Digital Evidence).
Towards Digital Skills for All Pre-service Teachers: Collecting Good Curricular Practices

The goal of this research full paper is to provide insight into most recent findings of interviews with faculty members teaching digital skills in an integrated and innovative way embedded into courses on subject didactics of a teacher education program. Pre-studies analyzing students' perspectives regarding the inclusion of digital competences in the teacher education program of a large Central-European university revealed that less than half of the students who were at an advanced stage in their studies felt sufficiently prepared to impart digital competences in their daily teaching. Given the importance of being digitally competent in the modern, digital era, the question arises, how digital competences can be sustainably included in the curriculum of a teacher education program. This paper analyzes interviews with five faculty members successfully teaching digital skills in concert with subject didactics of Geography in order to identify best practices for the integration of digital competences. The first author asked our Interview Partners to provide insight into the content they mediated, the integration of digital competences and tools in their courses, how their teaching could be further improved, and what challenges they encounter. Eventually, we looked for best practices and collected instructors' thoughts on improvements on a curricular level and examples of transferring the good practices to other subjects, such that future students could benefit from a better integration of digital competences. For this paper, we analyzed the data with a mixture of narrative analysis and thematic analysis. Improving the mediating of digital skills and competences in a wider range of subjects at the university level should eventually help students, and ultimately their students, to implement digital know-how such as modern teaching tools into their courses, making teaching more effective and computational thinking as well as related fields of computing more accessible to academic as well as secondary and younger students. The research so far has shown promising results considering examples of tools that can be used on a broad spectrum of subjects and lead to a factor of learned new digital competences if used properly. On the other hand, lecturers also warned about relying too much on technology in specific tasks such as orientation on a map or analyzing statistical data. We conclude that combining existing approaches with new, more modern didactics can be the key to transferring the competencies required for our students' future.
Novel E-Learning Experience and Perceptions with Impacts from Educational Key Opinion Leaders

In recent years, an increasing number of school-age children and adult learners are flocking to e-learning platforms or mobile Apps for personal or professional development. This research compared two studies that were built upon the constructivism model to investigate the parents, whose children are studying or have recently studied online, and also the adult learners' satisfaction, perceived learning outcomes, and recommendations towards Educational Key Opinion Leaders (Edu-KOLs). A two-phase study was designed specifically for both studies. We adopted the quantitative research approach using partial least squares structural equation modelling (PLS-SEM) to interpret the collected data. The findings revealed that for both learning cohorts, Edu-KOLs' knowledge level and course content has a significant influence on learners' perceived learning outcomes and customer advocacy and that higher engagement and interaction levels are favourably associated with their perception of Edu-KOLs. However, the e-learning platform played a positive role in selecting Edu-KOLs for parents but was not significant for adult learners. Perceived outcomes are critical for adult learners, whereas parents are satisfied as long as children are engaged, regardless of what they have learned.
ENHANCING THE EFFICIENCY OF THE LEVENSHTEIN DISTANCE BASED HEURISTIC METHOD OF ARRANGING 2D APICTORIAL ELEMENTS FOR INDUSTRIAL APPLICATIONS

The article addresses the challenge of reconstructing 2D broken pictorial objects by automating the search for matching elements, which is particularly relevant in fields like archaeology and forensic science. The authors propose a method to match such elements and streamline the search process by detecting and filtering out low quality matches. The study delves into optimizing the search process in terms of duration and assembly quality. It examines factors like comparison window length, Levenshtein measure margin, and number of variants to check, using theoretical calculations and experiments on synthetic elements. The experimental results demonstrate enhanced method effectiveness, yielding more useful solutions and significantly reducing the complexity of element comparisons by up to 100 times in extreme cases.