Reviewerly/exHarmony huggingface dataset:
Egra on Primary School in Serang City Banten; Strategies in Teaching Reading for Early Grade

The aims of the research is to find out the strategies in teaching reading for early grade students in primary school in reading Serang City Banten Indonesia. The strategies are determined from the results of the study using the instruments of Early Grade Reading Assessment (EGRA). The researchers used the quantitative research method by implementing the survey research design. The authors describe the obtained results of the student’s skill in reading components. As an example, we illustrate the proposed technique of teaching reading for primary school students. Our method allows to improve the student's reading ability is moderate; the children are less able to recognize; the meaningless word is still hard to be spelled; the students can understand the story well. The new strategies effectiveness evaluation is confirmed by the calculation the students recognize letters with a low reading speed about 2.02 minutes for 100 letters. The ability to read meaningful 32 words in 3 minutes, but the ability in reading a meaningless, the students got difficult 20 words in 3 minutes. The students reading in general are good with 88 percent, only a few students cannot read the text. The students can tell the contents of the reading by listening the story and retelling the story given orally in 80 percent. For the conclusion and the research results, the significance of this research is the stake holders of the education, both teachers and students in teaching and learning reading in primary school level. The newest ideas of this contribution is the initial efforts to teaching reading by determining students level of reading skill and decided the text leveling and facing and having treatment of the students classification nor only for the students that have already master the reading but also for the middle and lower skill students in reading by having various method of teaching reading such as reading aloud, reading together, and guiding reading. And providing various reading sources beside textbooks.
DESCRIPTIVE STATISTICAL CALIBRATION METHOD OF TRIAXIAL DIGITAL ACCELEROMETER ADXL345 AS EARTHQUAKES SENSOR

Seismic monitoring networks are the crucial elements in strong motion seismology for effective risk reduction. Low scale lateral variation of high intensity ground movement caused by earthquakes will be detected more effectively with densely located networks. However, the limitations of developing such project are rooted in expensive costs associated with the construction and installation in addition to bulky size of the conventional seismic observation system. Recently, micro-electromechanical system (MEMS) has being recognized in the applications of seismological and earthquake engineering due to the high precision obtained in these micron size semiconductor instruments and cheaper alternative for traditional seismic detector. ADXL345 is a type of digital triaxial MEMS accelerometer that is ideal for measurement of low-frequency vibrations and static accelerations of gravity, which makes it suitable for ground motion detection. Thus, this study aims at calibrating ADXL345 sensor that is required as sensing component in an affordable earthquake monitoring system with the Earthquake Benchmarking System (Penanda Aras Gempa Bumi, PAG) available in the inventory of Department of Mineral and Geoscience Malaysia, Sabah. Soil vibrations in EW (east-west or x-axis), NS (north-south or y-axis), and UD (up-down or z-axis) directions during random forces hit on the surface are recorded by both accelerometers. Acceleration magnitudes recorded by PAG and ADXL345 are extracted and data exploration is performed. Predominantly, ADXL345 measurements in horizontal and vertical ground movements are on a higher scale than the reference device. Subsequently, evaluation by using descriptive statistical analysis is chosen to produce numerical equations for data correction operations. İmplementation of the mathematical functions in ADXL345 for observing land movements in EW, NS, and UD directions resulted in decreasing the range values of output readings. Higher approximation of magnitudes of ground motion with the PAG system is achieved.
Cybersecurity Awareness, Cyber Human Values and Cyberbullying Among University Students in Selangor, Malaysia

The way that people use information technology is significantly influenced by how they view and feel about information security and computer ethics. A quantitative study was conducted through an online survey method to identify the relationships between cybersecurity awareness and cyber human values on cyberbullying among university students in Selangor, Malaysia. A total of 162 university students from two public universities in Selangor have participated in the study. The result of the study shows that cybersecurity awareness, cyber human values and cyberbullying were scored low by most of the respondents. Three aspects of cybersecurity awareness (password security awareness, social media use awareness and cyberbully awareness) were significantly correlated with cyberbullying (r=0.972, p&lt;0.00; r=0.166, p&lt;0.34, and r=-0.170, p&lt;0.03). In addition, cyber human values were also significantly correlated with cyberbullying (r=-0.192, p&lt;0.014). Besides, there was a significant difference in password security awareness (t=2.48, p&lt;0.014) and cyberbullying (t=1.99, p&lt;0.049) among male and female respondents. Finally, the overall regression model was statistically significant and password security awareness was found to be the most unique predictors of cyberbullying among the respondents (β= 0.968, p=0.000). This study noted that while respondents' knowledge of information technologies is greater, their understanding of cyber ethics is equally weaker. Hence, this study recommends that in order to lessen the context of cyberbullying, particularly among our youth, people must strike a balance between cybersecurity awareness and cyber human values. To increase awareness of cybersecurity and develop cybersecurity competence at all levels, ongoing education and advocacy efforts are crucial.
Impact of education digitalization and TIC in promoting social inclusion in universities

This research aims to examine how using digital tools and Technologies, Information, and communication (TIC) in higher education can help advance the goal of social inclusion. This study uses a qualitative and quantitative methodology to help in providing adequate results. The study also conducted descriptive analysis and cluster group effect to determine the relationship between the respondents in this study. This study surveyed 179 undergraduates at Peru's University of Lima and some of the data collected includes age, education level, and gender. As shown in the result, cluster 1 (chi-sqr = 29.78; p .001,max = 5.1), Cluster 2 (chi-sqr.= 99.6; p .001), and Cluster 3 (chi-sqr.= 13.1; p =.001). From the results, incorporating TIC into the classroom can have far-reaching effects on fostering social inclusion in higher education. However, several factors affect the extent to which digitization promotes social inclusion, such as the quality of the digital infrastructure, the digital competence of students and teachers, and the educational method is taken.
Persuasion-enhanced computational argumentative reasoning through argumentation-based persuasive frameworks

Abstract One of the greatest challenges of computational argumentation research consists of creating persuasive strategies that can effectively influence the behaviour of a human user. From the human perspective, argumentation represents one of the most effective ways to reason and to persuade other parties. Furthermore, it is very common that humans adapt their discourse depending on the audience in order to be more persuasive. Thus, it is of utmost importance to take into account user modelling features for personalising the interactions with human users. Through computational argumentation, we can not only devise the optimal solution, but also provide the rationale for it. However, synergies between computational argumentative reasoning and computational persuasion have not been researched in depth. In this paper, we propose a new formal framework aimed at improving the persuasiveness of arguments resulting from the computational argumentative reasoning process. For that purpose, our approach relies on an underlying abstract argumentation framework to implement this reasoning and extends it with persuasive features. Thus, we combine a set of user modelling and linguistic features through the use of a persuasive function in order to instantiate abstract arguments following a user-specific persuasive policy. From the results observed in our experiments, we can conclude that the framework proposed in this work improves the persuasiveness of argument-based computational systems. Furthermore, we have also been able to determine that human users place a high level of trust in decision support systems when they are persuaded using arguments and when the reasons behind the suggestion to modify their behaviour are provided.
Factors affecting English scores at national high school exam of sophomores at Thu Dau Mot University: Empirical evidence from GLS method

English, undeniably is now playing an extremely important role in many fields, particularly in cultural promotion and economic development of the country. Although the government has implemented several reforms to enhance the quality of nationwide English teaching and learning, the results, particularly shown through the national high school exams, are far below expectation. Therefore, as an effort to better the students’ score in the exam, this paper aimed at investigating factors, mostly those relating to students, affecting their scores at the national high school exams. To achieve that goal, data will be collected from 250 sophomores of Thu Dau Mot University through questionnaires. These students are chosen to get more reliable results because the latest NHE in 2021 was held amidst the coronavirus outbreak with lots of its unavoidable impacts. The generalized least squares (GLS) method is then used with eight independent variables and the dependent variable is the English score of these students in the National high school exam. Based on the findings, some recommendations are then made.
Optimizing the walk coin in the quantum random walk search algorithm

This paper examines quantum random walk search algorithm with walk coin constructed by generalized Householder reflection and additional phase shift factor. The results from numerical simulations with neural network show that, with such a construction of the walk coin, the algorithm is more robust to inaccuracies in the specific values of its parameters, as long as it is possible to control the phase difference between the phase shift factor and the phase involved in the Householder reflection. This paper explicitly shows how achieving a properly designed phase difference would make quantum random walk search on a hypercube more robust for coin register consisting of one, two and three qubits.
The Impact of Cryptocurrency on the Global Financial System: A Quantitative Investigation (2021)

Cryptocurrencies emerged as a disruptive and transformative force within the global financial landscape, challenging conventional banking systems and monetary policies.Her metrics such as market capitalization, trading volumes, and price volatility of cryptocurrencies, alongside their correlation with traditional financial assets and macroeconomic variables.The trading volumes of cryptocurrencies have attained substantial levels, indicating an escalating acceptance and adoption by investors and market participants.There are degrees of correlation, with certain cryptocurrencies exhibiting weak or negative correlations, while others exhibit stronger positive associations.There, underscoring the necessity of the intricate interactions between cryptocurrencies and macroeconomic factors.There is transformative influence exerted by cryptocurrencies on the global financial system.The researcher had considered people from financial sector to know the impact of cryptocurrency on the global financial system.The study concludes that there is significant impact of cryptocurrency on global financial system where Cryptocurrencies fostered financial inclusion for individuals lacking access to traditional banking services and elevated economic and social standing.
Emerging Technology Opportunities and Challenges towards Organization and National Development

Emerging technologies are playing a significant role in driving organization and national development. As these technologies continue to evolve, the opportunities and challenges associated with them rises. Current study aiming to identify the emerging technology opportunities and challenges towards organization and national development in the context of Malaysia. To achieve the objective, current study has deployed secondary qualitative analysis method with literature review approach. Based on the analysis, study finds that, AI, Blockchain and IoT are the most emerging technology that has significant contribution toward the organizational and national development. Study further, identified potential challenges and the showcase the potential process to avail opportunities of emerging technologies. Artificial Intelligence (AI) can help companies to automate their operations, reducing errors and increasing profitability. Automation can also enhance the quality of products, as machines are less prone to human error. Blockchain technology can provide a secure and efficient way to conduct transactions, making it possible for businesses to reach new markets and expand their customer base. Technologies like solar energy and wind turbines can help reduce the country's dependence on fossil fuels, which is important for the long-term sustainability of the environment. Another significant challenge is the lack of infrastructure to support the implementation of emerging technologies. Additionally, the lack of regulations for emerging technologies poses a challenge for organizations and the government, especially in areas such as data privacy and security. The government and organizations must work together to ensure that the public is informed about the benefits and challenges of these technologies. Therefore, these technologies can promote sustainable development and provide new business opportunities. In conclusion, the challenges that need to be addressed to fully leverage the benefits of emerging technologies, including the lack of skilled workers, infrastructure, and regulations in Malaysia would be discussed.
Methodological Exploration of Cartoon-based Qualitative Research

본 연구는 만화의 고유한 특성이 질적연구에서 유용하게 활용될 가능성을 높게 평가하여 질적연구에서 만화를 활용하고자 하는 연구자들을 위해 만화 기반 질적연구의 방법을 개괄적으로 소개한다. 만화의 특징을 분석하여 질적연구에서 만화 활용의 유용성에 대해 논의하였으며, 만화 기반 질적연구의 역사적 맥락과 흐름을 분석함으로써 이 연구 방법에 대한 포괄적인 이해를 형성하고, 선행연구를 통해 만화 기반 질적연구의 특징을 살펴보았다. 질적연구에서 만화는 복잡한 아이디어를 간단하고 매력적인 방식으로 전달하는 데 사용할 수 있으며, 언어 장벽을 극복하는 데 도움이 될 수 있다. 만화는 연구자나 연구 참여자의 감정적인 반응을 이끌어내기 위해 효과적으로 사용될 수 있고, 다양하고 포괄적인 연구를 가능하게 한다는 이점이 있다. 만화 기반 질적연구의 단계는 연구문제 정의 및 문헌 검토, 연구방법 설계, 자료수집, 자료분석, 해석 및 연구 결과 표현의 과정을 거칠 수 있다. 각 단계에서 만화는 데이터로써, 또는 참여자의 유도, 면담 기록의 재해석, 사건의 배열, 연구 결과의 표현물 등으로 활용될 수 있다. 질적연구에서 만화를 활용하는 것은 복잡한 사회 현상에 대한 이해를 풍부하게 하고, 창의적이며 효과적인 지식 전달의 가능성을 높일 수 있다.This study provides an overview of the method of cartoon-based qualitative research for researchers who want to utilize comics in qualitative research because the unique characteristics of comics have the potential to be useful in qualitative research. We discuss the usefulness of using comics in qualitative research by analyzing the characteristics of comics, analyze the historical context and flow of comics-based qualitative research to form a comprehensive understanding of this research method, and examine the characteristics of cartoon-based qualitative research through previous studies. In qualitative research, comics can be used to convey complex ideas in a simple and engaging way, and can help overcome language barriers. They can be used effectively to elicit emotional responses from researchers and research participants, and have the advantage of allowing for diverse and inclusive research. The stages of cartoon-based qualitative research can include defining the research problem and reviewing the literature, designing the research method, collecting data, analyzing the data, interpreting the data, and presenting the findings. At each of these stages, comics can be used as data or as a means of eliciting participants, reinterpreting interview transcripts, arranging events, and presenting findings. The use of comics in qualitative research can enrich our understanding of complex social phenomena and increase the potential for creative and effective knowledge transfer.
Performance evaluation of multivariate statistical techniques using edge-enabled optimisation for change detection in activity monitoring

Abstract The monitoring of human activities using simple body worn sensors is an important and emerging area of research in machine learning. The sensors capture a large amount of data in a short period of Time in a relatively un-obtrusive manner. The sensor data might have different transitions to be used for deification of different user activities. Therefore, change point detection can be used to classify the transition from one underlying distribution to another. The automatic and accurate change point detection is not only used for different events, however, can also be used for generating real world datasets and responding to changes in patient vital signs in critical situation. Moreover, the huge amount of data can use the current state-of-the-art cloud and edge computing platforms to process the change detection locally and more efficiently. In this paper, we used multivariate exponentially weighted moving Average (MEWMA) for online change point detection. Additionally, genetic algorithm (GA) and particle swarm optimization (PSO) is used to automatically identify an optimal parameter set by maximizing the F-measure. The optimisation approach is implemented over an edge cloud platform so that the data can be processed locally and more accurately. Furthermore, we evaluate our approach against multivariate cumulative sum (MCUSUM) from state-of the-art in terms of different metric measures such as accuracy, precision, sensitivity, G-means and F-measure. Results have been evaluated based on real data set collected using accelerometer for a set of 9 distinct activities performed by 10 users for total period of 35 minutes with achieving high accuracy from 99.3% to 99.9% and F-measure up to 62.94%.
BRAILE Reading Device for the Deaf and Blind using Real Time Speech

Braille is a vital means of communication; it is a system for blind people, one of touch reading and writing in which Raised dots are impressions that represent the letters of the alphabet.It is an extremely important tool for blind people to educate themselves, and it is a critical component that supports not only educational advancement, but sub-consequently increases employment prospects.The blind and deaf should be taught Braille to be able to become literate, which is a necessity in today's world.Braille is a much harder language than sign, as there are a lot of combinations of the impressions of the six raised dots that are not easy to memorize.Visually impaired people are required to master skills to communicate through Braille text, which itself is really time-taking and cumbersome task.In addition, other people need to learn the same set of skills to understand and respond to the visually impaired person.We have devices that convert text to Braille language as well as real-time Braille to speech using Raspberry Pi camera and a Raspberry Pi.Other devices use FPGAs/Arduinos for converting speech to braille.
Detection of Face Masks in Real Time

Real-time face mask detection has become a crucial task in ensuring public safety and adherence to maskwearing guidelines.In this project, we present a system for real-time face mask detection using Python.The system utilizes computer vision techniques and deep learning algorithms to accurately identify whether individuals in a video stream are wearing masks or not.Our approach involves leveraging the OpenCV library for real-time video processing and face detection.We employ a pre-trained convolutional neural network (CNN) model, such as MobileNetV2 or ResNet, for mask classification.The CNN model is trained on a large dataset of annotated face images with and without masks.The face mask detection system works by capturing video frames from a camera feed, detecting faces using Haar cascades or deep learning-based methods, and applying the trained CNN model to classify the presence or absence of masks on each detected face.The system provides real-time feedback, overlaying bounding boxes and labels indicating whether a face is wearing a mask or not.To enhance the system's performance and accuracy, we employ data augmentation techniques during training, which help in handling variations in lighting conditions, poses, and backgrounds.Additionally, we optimize the model for real-time execution, taking advantage of hardware acceleration technologies like GPU processing when available.Through experimental evaluations on various video streams and datasets, our system demonstrates high accuracy and efficiency in real-time face mask detection.It offers a reliable solution for monitoring mask compliance in public spaces, such as airports, hospitals, retail stores, and public transportation, contributing to the prevention of the spread of infectious diseases.
DERMATOLOGICAL DISEASE DETECTION USING IMAGE PROCESSING TECHNIQUE: A SURVEY

Dermatological diseases represent a significant health concern, and their timely and accurate detection is crucial for effective treatment.Image processing techniques have emerged as valuable tools in dermatology, enabling automated disease detection and analysis.This survey explores the use of image processing methods for dermatological disease detection, focusing on various aspects such as image segmentation, feature extraction, and classification algorithms.The survey covers a range of studies and highlights the advancements made in this field, showcasing the potential of image processing in improving dermatological disease diagnosis.
Comparison of the Fisher-Yates Shuffle and the Linear Congruent Algorithm for Randomizing Questions in Nahwu Learning Multimedia

Nahwu Quiz is a basic Arabic learning application that can be played by the public over the age of 12 years. In the question practice menu, there are questions and 4 multiple choice questions. The user only needs to choose one of the multiple choices that the user thinks is correct/matches the question at hand. In one game, there are 5 questions. After answering all these questions, you will immediately see the score. The purpose of developing this application apart from being a medium of entertainment as well as a medium of learning and memory training for game users (users). To make this Nahwu Quiz application, the authors use the Fisher Yates Shuffle (FYS) algorithm which is used to perform the randomization function in multiple choice and the Linear Congruent Method (LCM) algorithm as a comparison. White box and black box testing were applied to see the feasibility of the program and to obtain efficiency in the comparison of randomization methods. The results of white box and black box testing on the application show that the application is feasible. with reference to the white box test results that the FYS algorithm and the LCM have the same complexity as the result of cyclomatic complexity = 2.