Reviewerly/exHarmony huggingface dataset:
Queueing Model based Dynamic Scalability for Containerized Cloud

Cloud computing has become a growing technology and has received wide acceptance in the scientific community and large organizations like government and industry.Due to the highly complex nature of VM virtualization, lightweight containers have gained wide popularity, and techniques to provision the resources to these containers have drawn researchers towards themselves.The models or algorithms that provide dynamic scalability which meets the demand of high performance and QoS utilizing the minimum number of resources for the containerized cloud have been lacking in the literature.The dynamic scalability facilitates the cloud services in offering timely, on-demand, and computing resources having the characteristic of dynamic adjustment to the end users.The manuscript has presented a technique which has exploited the queuing model to perform the dynamic scalability and scale the virtual resources of the containers while reducing the finances and meeting up the user's Service Level Agreement (SLA).The paper aims in improving the usage of virtual resources and satisfy the SLA requirements in terms of response time, drop rate, system throughput, and the number of containers.The work has been simulated using Cloudsim and has been compared with the existing work and the analysis has shown that the proposed work has performed better.
The Impact of COVID-19 on Digital Competence

The study looked into how COVID-19 affected the digital competence of a group of preservice teacher education students at a higher education institution in the Sultanate of Oman.The paper examined students' digital profile in five areas namely information and data literacy, communication and collaboration, digital content creation, safety and problem solving.Data from 32 undergraduate students was collected by utilizing DigComp, a European Commission digital skills selfassessment tool and findings from a survey.The digital competence framework measures the set of skills, knowledge and attitudes that describes what it means to be digitally competent.These skills are important for students to be effective global citizens in the 21 st century.The results of the study revealed that the majority of the students scored Level 3 (Intermediate) in their self-assessment competency test score.The majority of the students perceived that their digital competence improved significantly as the result of online learning which was accelerated by the COVID-19 pandemic.The rationale of this investigation is that it helps educators understand the students' level of digital competence and the students' perspectives on ICT skills.In turn, it informs us the ways to monitor the students' digital progress and the next steps in developing their digital competency.
An Improved Breast Cancer Classification Method Using an Enhanced AdaBoost Classifier

The goal of this research is to create a machine learning (ML) classifier that can improve breast cancer (BC) diagnosis and prediction.The principle components analysis (PCA) technique is used in this work to minimize the dimensions of the BC dataset and achieve better classification metrics.The developed classifier outperformed others in terms of F1 score and accuracy score.Using the original BC dataset, four different classifiers are applied to determine the best classifier in terms of performance metrics.The used classifiers were RandomForest, DecisionTree, AdaBoost, and GradientBoosting.The RandomForest classifier obtained (95.7%) f1 score and (94.5%) accuracy score, the DecisionTree classifier obtained (93%) f1 score and (91%) accuracy score, the GradientBoosting classifier obtained (95%) f1 score and (93.5%) accuracy score, and the AdaBoost classifier obtained (95.8%) f1 score and (94.5%).The AdaBoost classifier was utilized to create the final model using the reduced PCA dataset because it scored the highest performance metrics.The developed classifier is named as "pcaAdaBoost".The optimized pcaAdaBoost achieved higher performance metrics in terms of f1 score (99%) and accuracy score (98.8%).The results reveal that the optimized pcaAdaBoost scored highest performance measures in terms of crossvalidation and testing outcomes, with an overall accuracy of (99%).The improved results justify the use of dimensionality reduction in high-dimension datasets to reduce complexity and improve performance measures.
DiffSTG: Probabilistic Spatio-Temporal Graph Forecasting with Denoising Diffusion Models

Spatio-temporal graph neural networks (STGNN) have emerged as the dominant model for spatio-temporal graph (STG) forecasting. Despite their success, they fail to model intrinsic uncertainties within STG data, which cripples their practicality in downstream tasks for decision-making. To this end, this paper focuses on probabilistic STG forecasting, which is challenging due to the difficulty in modeling uncertainties and complex ST dependencies. In this study, we present the first attempt to generalize the popular denoising diffusion probabilistic models to STGs, leading to a novel non-autoregressive framework called DiffSTG, along with the first denoising network UGnet for STG in the framework. Our approach combines the spatio-temporal learning capabilities of STGNNs with the uncertainty measurements of diffusion models. Extensive experiments validate that DiffSTG reduces the Continuous Ranked Probability Score (CRPS) by 4%-14%, and Root Mean Squared Error (RMSE) by 2%-7% over existing methods on three real-world datasets.
Pengaruh Penggunaan Media Pembelajaran Puzzle Terhadap Hasil Belajar Siswa Mata Pelajaran Matematika Materi Bangun Datar Kelas II SD Inpres Belang

This study aims to determine the positive effect of using doraemon pouch learning media in improving student learning outcomes in learning mathematics multiplication material for class III students of SDI Belang. This research is a quantitative research. The research method used was pre-experimental using a one-group pretest posttest design. The sample in this study were 20 people. Data collection techniques in this study used tests, observations, and documentation. The results of this research classically show that the average post-test score of students increases after using learning media for Doraemon bags compared to the average pre-test score. The data analysis technique used is statistical analysis of pared samples with the help of the SPSS program. The results of the study show sig = 0.006 ≤ 0.05, it is said that there is a significant difference between the results of the pre-test and post-test which indicates that the alternative hypothesis proposed by the researcher is accepted, namely that there is a positive and significant influence on the use of learning media in Doraemon's pouch in improving learning outcomes students in learning mathematics multiplication material for class III students at SDI Belang.
Pengaruh Penggunaan Media Kantong Doraemon dalam Meningkatkan Hasil Belajar Matematika Materi Perkalian Kelas III SDI Belang

This study aims to determine the positive effect of using doraemon pouch learning media in improving student learning outcomes in learning mathematics multiplication material for class III students of SDI Belang. This research is a quantitative research. The research method used was pre-experimental using a one-group pretest posttest design. The sample in this study were 20 people. Data collection techniques in this study used tests, observations, and documentation. The results of this research classically show that the average post-test score of students increases after using learning media for Doraemon bags compared to the average pre-test score. The data analysis technique used is statistical analysis of pared samples with the help of the SPSS program. The results of the study show sig = 0.006 ≤ 0.05, it is said that there is a significant difference between the results of the pre-test and post-test which indicates that the alternative hypothesis proposed by the researcher is accepted, namely that there is a positive and significant influence on the use of learning media in Doraemon's pouch in improving learning outcomes students in learning mathematics multiplication material for class III students at SDI Belang.
Response Analysis of Training Participants in Making E-Module Using Flip PDF Corporate for Teachers at SD IT Insan Mulia, Bengkulu City

This study aims to discuss the success rate of training activities based on the results of the response analysis of training participants in making e-modules using flip pdf corporate for teachers at SD It Insan Mulia, Bengkulu City. This research was conducted in July-August 2022. The target audience for this service activity is the education community. namely SD IT Insan Mulia, Bengkulu City. The target of this service is the teachers at SD IT Insan Mulia, Bengkulu City who will benefit from this training activity. In the plan for this service activity, observations have been made and the adequacy of facilities and infrastructure for training activities and there is support from the school which states that it welcomes this service activity to be carried out at SD IT Insan Mulia, Bengkulu City. The activity began with observations and interviews with a number of teachers and principals of SD IT Insan Mulia, Bengkulu City about the needs needed to assist teachers in making electronic teaching materials, especially those that can be used in the midst of the current pandemic. To measure the success of this activity, the team conducted evaluations and surveys in the form of questionnaires distributed to teachers. These results were then analyzed descriptively. The training activity for making e-modules using a corporate flip pdf for teachers at SD IT Insan Mulia, Bengkulu City was successfully carried out, this was evidenced by the positive response from the training participants to the training activities shown through the answers selected on the response questionnaire sheet.
The use of i-THINK Mapping in teaching reading comprehension among ESL teachers

This study investigated the use of i-THINK Mapping in teaching reading comprehension by ESL teachers to a group of Form Five students, and the factors and challenges the ESL teachers faced in teaching reading comprehension using i-THINK Mapping. A qualitative approach, specifically a case study design, was employed in this study. Classroom observations, semi-structured interviews, and document analysis of their lesson plans were used to collect the data. Four ESL teachers with a minimum of 5-year teaching experience in a rural secondary school in Hulu Selangor, Malaysia, were selected using a purposive sampling technique to participate in this study. Thematic analysis was used to analyse the data obtained from classroom observations and interviews. The findings show that the teachers had applied five i-THINK maps, including a Circle Map to define in context, a Bubble Map to describe, a Double Bubble Map to compare and contrast, a Flow Map to show the sequence of an event, and a Tree Map to classify different ideas. The i-THINK Mapping motivated the students to discuss, brainstorm, and cooperate with their peers to detect the details from the given reading texts. The teachers’ challenges include the time constraints in preparing the lesson with i-THINK Mapping and a low level of student English proficiency. One implication of this study is that teachers’ use of i-THINK Mapping to teach reading comprehension could assist students in generating ideas, expanding ideas, and expressing them orally.
Uncovering EFL learners’ demotivation towards English online learning during the Covid-19 pandemic in Indonesia

Online learning during the Covid-19 pandemic has demotivated Indonesian tertiary EFL students to learn English, which affected their English performance and achievement. This article ferrets out the features of the EFL students’ demotivation, the factors affecting their demotivation, the solution to reduce their demotivation, and the implication of their demotivation towards their English performances and achievement. The data for this descriptive quantitative research were collected through an online open-ended questionnaire to the EFL students of two Islamic state colleges in East Java, Indonesia. The questionnaire was distributed when the Covid-19 pandemic was still at its peak. There were 71 out of 76 respondents who completed the questionnaire claimed to experience demotivation with online learning mode. The data from those 71 respondents were then analyzed descriptively. The results of this study indicate that online learning experiences were found to be the main factor that affected their demotivation. This was further evident in their English performance and achievement. Meanwhile, the aspects of teachers, online learning infrastructures, family, and student-related demotivators contributed to conducting effective online learning. This study utilized qualitative data from the learners’ perspective so that further studies which take a different perspective, such as family, teachers, lecturers, and policymakers, would enrich these findings.
COVID-19 Impacts: Empirical Studies on Orion Indoor Sports Business Using Visual Analytics

Covid-19 spreads across the world in just a few months and it has caused severe economic consequences to many countries. Many businesses are also affected dramatically due to the lockdown in order to stop the spread. It does not only affect businesses, it affects how consumers behave in buying and shopping as well. Consumers learn to improvise and get used to the new habits. For example, consumers are not allowed to go to the gyms as they are closed during the lockdown, and they start to work out at home. Technology advances has played a big role in helping the consumers to cope in this situation in an innovative way. Some changes done in an organization to adapt to the pandemic can potentially improve their business tremendously and reduce the losses that already exist before the pandemic. For example, gym equipment sales were only targeting business before the pandemic. However, due to the lockdown, many people were left nowhere to work out and they then prefer to buy gym equipment at home. This will increase the demand of gym equipment and thus boosting the fitness industry business. With the advancement of technology, fitness industry can sell their products online easily and they can also view real-time business performance.&#x0D;
"UNION" OF AN ARTIST WITH A NON-HUMAN AGENT: UTOPIA OR A WORKING MODEL OF ARTISTIC PRODUCTION?

The subject of the article: works of contemporary art created by non-human agents, on the example of which one can analyze the ways of interaction of contemporary artists with non-trivial media (algorithms, robots, "half-life artists", etc.). The object of the article: the impact of technological innovations on contemporary art production, as well as the need, in connection with the artist's appeal to science and the latest technologies, to rethink the goals and objectives of communication through images and the very concept of art. The purpose of the project: to update the information for the scientific world about the strategies of interaction between a human artist and a non-human agent, as well as about the nature of this interaction. Results of the work: the study showed that the creation of a work of art (both physical and as part of a post-production strategy, as a re-significance) – despite the criticism of anthropocentrism by representatives of the Actor-Network Theory and individual media theorists, should still be understood as purposeful activity inherent in a human, but not in a non-human agent. Appeal to non-human agents can be considered within the framework of the paradigm of "assistive technologies" and "chimerical" actor. Scope of the results: expanding the boundaries of the application of art history methodology and related disciplines, which contributes to the development of a language for describing the phenomena of contemporary art in the interdisciplinary field of modern media, in particular, in the dynamically developing field of art &amp; science. Conclusion: Based on the results of this study, key trends were identified that determine the nature of our interaction with the other in the process of creating a work of art and interacting with it.
Sistem Monitoring Pasang Surut Air Laut Berbasis Web Menggunakan Fuzzy Logic Pada Kuala Langsa

Abstract - Tides are a phenomenon of periodic and periodic ups and downs of sea level movements. The tidal period is the time between the crest of a wave to the crest of the next wave, the time of the tidal period varies from 12 hours 25 minutes to 24 hours 50 minutes. Information about tides is very useful for activities related to the marine world. In the area of ​​​​Kuala Langsa, tides often occur, fishermen and anglers in Kuala Langsa only rely on the poles of residents' houses to determine the time of the tide. The system is made useful so that fishermen and anglers can find out the time and state of the tides using smartphones, by creating a “Sea Tidal Monitoring System using Ultrasonic Sensors and nodeMCU which can provide results of monitoring the time and tidal status in Kuala Langsa and will displayed on a Web page”. Ultrasonic sensors can detect well and can provide tidal data to be displayed on a web page and can be accessed using smartphones and other devices during the testing period in Kuala Langsa village, Langsa City with 62.5% success being tested.
The Use of Video as an Authentic Materials in Improving Students’ Writing Skills of Recount Text

This research was purposed to measure the significant difference on the use of video as an authentic material to improve students’ writing skills and investigate the use of video as authentic material in students’ writing skills on recount text. The present study applied cluster random sampling technique that implemented a mixed-method with the type of true-experimental design. A series of pretest-posttest for the quantitative data and interview for the qualitative data were utilized. The sample of the present study employed 30 students as the experimental and control group. The documentation of students’ tests was used to extract the data. The result showed that there was significant difference in students’ writing skills before and after being taught by means of video as an authentic material. Meanwhile, the interview showed that students with high, middle and low achiever gave positive responses about using video as an authentic material in improving writing recount text. The study concluded that the use of video as an authentic material has contributed a good impact to students’ writing recount text with high, middle and low achiever, although it did not give significant impact in students’ learning outcomes particularly in writing recount text.
Prediction of Drug Concentration in Human Bloodstream using Adams-Bashforth-Moulton Method

Pharmaceutical drugs are chemicals intended to avoid, assess, heal, or cure a disease. It is also commonly referred to as medication. When medicine is taken, it gets absorbed into the bloodstream, spreads throughout the body, and achieves its maximum concentration. Following this, the medication level gradually decreases as it is removed from the body. The drug concentration according to the time can be predicted using mathematical concepts and pharmacokinetic models. The compartmental model is a fundamental type of model used in pharmacokinetics. The number of compartments required to describe the drug's action in the body is one-compartment, two-compartment, and multicompartment. These models can forecast medication concentrations in the body over time. This paper will focus on the one-compartment model and Adams Bashforth-Moulton method. Adams Method is one of the linear multistep techniques applied to solve numerical ordinary differential equations that contain the predictor method (Adams Bashforth) and corrector method (Adams Moulton). The integrated development environment used for the computation and graphing is MATLAB. The expected result of this report is that we can predict the concentration of the chosen drugs over time and how long a particular person needs to wait before donating blood safely.
Learning Choice Functions with Gaussian Processes

In consumer theory, ranking available objects by means of preference relations yields the most common description of individual choices. However, preference-based models assume that individuals: (1) give their preferences only between pairs of objects; (2) are always able to pick the best preferred object. In many situations, they may be instead choosing out of a set with more than two elements and, because of lack of information and/or incomparability (objects with contradictory characteristics), they may not able to select a single most preferred object. To address these situations, we need a choice-model which allows an individual to express a set-valued choice. Choice functions provide such a mathematical framework. We propose a Gaussian Process model to learn choice functions from choice-data. The proposed model assumes a multiple utility representation of a choice function based on the concept of Pareto rationalization, and derives a strategy to learn both the number and the values of these latent multiple utilities. Simulation experiments demonstrate that the proposed model outperforms the state-of-the-art methods.
THE PERCEPTION OF ISLAMIC RELIGIOUS EDUCATION STUDENTS ON KAHOOT! AS A QUIZ

Kahoot! is the most popular online platform in universities to increase student participation in class. The application is suggested as an instrument for the assessment of learning outcomes. This study aims to determine the level of perception of Islamic religious education students towards Kahoot! as a quiz in the midterm exam. The research approach used is descriptive qualitative with questionnaire and observation data collection techniques. The data were then analyzed using descriptive statistics by presenting the data in the form of tables and diagrams. Based on the results of the study, it can be concluded that students' perceptions are very positive in terms of three main indicators, namely the ease of understanding how the application works, the ability of the application to involve participants, and the relevance of quizzes to learning activities. Most students think that Kahoot! provide new experiences that are interesting, fun, and challenging. They are motivated and actively participate in taking quizzes.
Experimental Demonstration of Quantum Overlapping Tomography

Quantum tomography is one of the major challenges of large-scale quantum information research due to the exponential time complexity. In this Letter, we develop and apply a Bayesian state estimation method to experimentally demonstrate quantum overlapping tomography [Phys. Rev. Lett. 124, 100401 (2020)PRLTAO0031-900710.1103/PhysRevLett.124.100401], a scheme intent on characterizing critical information of a many-body quantum system in logarithmic time complexity. By comparing the measurement results of full-state tomography and overlapping tomography, we show that overlapping tomography gives accurate information of the system with much fewer state measurements than full-state tomography.