Reviewerly/exHarmony huggingface dataset:
Improving Mass Detection in Mammography Using Focal Loss Based RetinaNet

Breast cancer is a significant global health issue and plays a crucial role in improving patient outcomes through early detection. This study aims to enhance the accuracy and efficiency of breast cancer diagnosis by investigating the application of the RetinaNet and Faster R-CNN algorithms for mass detection in mammography images. A specialized dataset was created for mass detection from mammography images and validated by an expert radiologist. The dataset was trained using RetinaNet and Faster R-CNN, a state-of-the-art object detection model. The training and testing were conducted using the Detectron2 platform. To avoid overfitting during training, data augmentation techniques available in the Detectron2 platform were used. The model was tested using the AP50, precision, recall, and F1-Score metrics. The results of the study demonstrate the success of RetinaNet in mass detection. According to the obtained results, an AP50 value of 0.568 was achieved. The precision and recall performance metrics are 0.735 and 0.60 respectively. The F1-Score metric, which indicates the balance between precision and recall, obtained a value of 0.66. These results demonstrate that RetinaNet can be a potential tool for breast cancer screening and has the potential to provide accuracy and efficiency in breast cancer diagnosis. The trained RetinaNet model was integrated into existing PACS (Picture Archiving and Communication System) systems and made ready for use in healthcare centers.
A Comparative Move Analysis of Low and High-Impact Social Science Scopus Journal Articles Written by Reputable Indonesian Authors

Producing research articles requires clearly, logically, rationally, and empirically substantiating complicated ideas. Regarding that, many professors struggle to have their articles published in highly regarded publications and require references; for instance, the rhetorical move pattern. Many studies have analyzed the rhetorical structure of articles, but few have investigated the rhetorical move of the research articles produced by lecturers by specifically comparing their publications in high-impact versus low-impact Scopus-indexed journals. Using a descriptive-comparative qualitative design, this study seeks to investigate the moves of low-impact and high-impact articles of the two social humanities lecturers of a state university in Indonesia. Eight articles were analyzed through the move framework proposed by Maswana (2015). The results revealed that the rhetorical moves from each section were organized with significant conformities and minor non-conformities.Especially, the authorsemphasized the goals, procedures, and outcomes of the publications in the abstract section. Furthermore, the writers provided references to the existing literature and the goal of the research to assist the reader in understanding the theory applied in the papers. On the other hand, deviations from the norm are displayed in the methodology section due to variations in how the study was conducted, particularly the data processing phase. The authors’ attention to conveying the research’s specific findings and their significance was in the findings and discussion section. The results of this study can be used as a reference for Indonesian researchers who are striving to publish papers in international journals toward a more visible and impactful publication.
Promoting EFL Students’ Speaking Performance through ELSA Speak: An Artificial Intelligence in English Language Learning

The presence of a technology-based speech learning application namely English Language Speech Application (ELSA), an artificial intelligence (AI) may promote EFL students' speaking performance because of its great features. This research attempts to examine EFL students' speaking performance by using the ELSA speak application, further explore their perceptions of using it, and find out the inhibiting factors influencing low performance in their speaking. A mixed-method research design was applied to obtain both quantitative and qualitative data. 21 EFL students (5 Males and 16 Females) from Universitas Teknologi Yogyakarta were involved in the data gathering process which was collected by using a test, questionnaire, and semi-structured interview. Furthermore, pre-test and post-test were conducted to examine their speaking ability, and a questionnaire using a 4-point Likert scale. In addition, a semi-structured interview was conducted to further explore the inhibiting factors of their low speaking performance. The findings revealed that students' speaking ability has significantly improved after using the ELSA application. It can be known the mean score of pre-test results was 75, meanwhile, the post-test score was 88. There was a 17% improvement after using the ELSA application. Furthermore, of 20 respondents, 18 (90%) of respondents feel confident in speaking English by using the ELSA Speak application. Only 2 (10%) of the respondents disagree and none strongly disagree about the statement. Of 20 respondents, 16 or 80% of respondents have positive perceptions that using ELSA may increase their speaking performance. Moreover, of 20 respondents, 19 or 95% of respondents perceived ELSA to be a great speech application that could boost their motivation to improve their speaking performance. 18 or 90% of respondents perceived that this application has a good quality learning design. Meanwhile, internal and external factors were identified as the inhibiting factors influencing their low speaking performance.
Developing Problem-Based Inquiry Model in Indonesian Learning in General High Schools

This research is motivated by the importance of collaboration between teachers and students in learning Indonesian. This collaboration is marked by cooperation in improving the quality of learning by designing inquiry-based Indonesian language learning model books. This model book is designed to be more attractive to educators and students by considering the content and design to suit the needs and characteristics of students. This research aims to develop an inquiry-based Indonesian language learning model that is viewed from the aspects of validity, practicality and effectiveness. The research uses research and development methods using the Plomp model which consists of preliminary research, prototypes and assessment. Research findings reveal that the model developed produces high validity seen from the results of expert assessments, while the practicality of the model shows very high results seen from teacher assessments when testing this model. Apart from that, the effectiveness of the model is very effective as seen from the presentation of this model which is clear and well organized, the language used is easy to understand, and the structure of the model is attractive. Overall, this model can be applied well in Indonesian language learning, because it can improve student learning outcomes.
Development of Inquiry-Based Teaching Materials on Environmental Pollution to Improve High School Students' Environmental Literacy Skills

This research aims to produce inquiry-based e-teaching materials on environmental pollution to improve student's literacy skills in terms of validity, effectiveness, and practicality. This study used the research and development (R&amp;D) method with the ADDIE model. This study was carried out in a senior high school in Cimahi. The e-teaching materials trial was conducted in two classes, with the experimental class using e-teaching materials and the control class as a comparison using traditional school textbooks. The e-book validation instrument used in this study was a questionnaire sheet. Validation analysis was the data analysis method employed, and the t-test and N-gain were utilized to examine the effectiveness of the instructional materials. The study's findings demonstrated that the inquiry-based teaching materials on environmental pollution material were declared valid and suitable for use in the biology learning process. According to the outcomes of employing inquiry-based e-teaching resources to enhance environmental literacy abilities, the experimental class's N-gain value was higher than the average n-gain value for the control class. Therefore, inquiry-based online teaching resources are practical and effective at enhancing students' environmental literacy abilities.
Enhancing Writing Report Texts Using Padlet Website: The Perceptions

There are several technology-based solutions available to help students with disabilities related to compose something. However, merely providing access to technology is insufficient. It is important to utilized technology because the impelentation of using technology have an impact on students’ outcomes. The aim of this study is to investigate the perceptions in utilizing Padlet as a learning medium in writing report texts. Descriptive qualitative method was employed using questionnaire and interview. They were distributed through 36 sample of grade X and one teacher. 78% of the participants had positive perceptions; 19% neutral and 3% negative. It assumed that most of the students found that using Padlet website provided a more engaging and interactive writing experience. It was also revealed that the students who gave feedback negative and neutral perceptions had another argument that there are more learning media instead of Padlet which can increase his writing skill. The teacher supported the findings and provide nine description on how she perceived Padlet as learning media. Overall, using Padlet as a collaborative writing approach has the potential to connect and develop students' writing skills. This study is useful for writing teachers since the benefits of Padlet can make the writing process more effective and engaging, which relates to 21st Century Teaching and Learning.
Literasi Digital Guru Dalam Pembelajaran Daring di Sekolah Dasar

This study examines the components of digital literacy and teachers' efforts to improve digital literacy at SD Muhammadiyah Kalipakem 1 Yogyakarta. This research method used a case study with a qualitative approach. Data was collected through interviews with school principals, teachers, and students and was supported by observation and documentation data. Data was analyzed using an interactive model, including data display, reduction, and verification/drawing conclusions. The results of the study showed that: 1) the teacher's digital literacy component consists of the teacher as an educational content creator, communication between teachers and students in online learning, online learning management skills, teachers' attitudes towards the importance of digital competence, integration between reference search abilities and material development, use of platforms in conducting learning evaluations and increasing student digital literacy. 2) Teachers used various methods to improve digital literacy competence, namely by making independent efforts, utilizing teacher work group forums (KKG), and the role of the school principal.
Pengembangan Bahan Ajar Digital dengan Pendekatan Collaborative Learning Menggunakan Padlet untuk Meningkatkan Writing Skills Siswa

This research aims to analyze the feasibility and effectiveness of digital teaching materials with a collaborative learning approach using Padlet to improve students' ability to write explanatory texts. This research used research and development methods with a 4D model. The subjects of this research were Nida El-Adabi Islamic Middle School students in class VIII. Interviews, observations, and questionnaires were data collection instruments, then analyzed using percentage analysis techniques and the N-Gain effectiveness test. This research showed that the material test results obtained an average percentage of 90.9% (very feasible), and the media test results obtained 65.5% (feasible). In the assessment of one-to-one student trials, the score was 81.77%, while for small group trials, it was 88.02%. In the effectiveness test, it was found to be 81.55% (very feasible). The results of the initial writing ability assessment of the participants got a score of 75.83, and the results of the students' responses after the development got a score of 86.97. Developing digital teaching materials to improve writing skills using a collaborative learning approach using Padlet is very suitable for helping students improve their writing skills.
Hedges and Boosters in Student Scientific Articles within the Framework of a Pragmatic Metadiscourse

The ability of students to edit scientific papers is still low, especially in mastering the use of hedge (fencing devices) and boosters (strengthening devices). Hedges and boosters are forms of expression of the author's attitude towards propositional content through epistemic modalities. This study aims to describe hedges and boosters in student scientific articles within the framework of a pragmatic metadiscourse. A qualitative descriptive approach was used in this study. The data used is in the form of editing words, sentences, and paragraphs in scientific articles editing courses. The source of this research data is a scientific article by PGRI Adi Buana University Surabaya students in 2022. Data collection techniques use documentation techniques and recording techniques. Data analysis techniques to identify hedges and word lists of boosters using the AntConc application built by Lawrence Anthony. Data that has been obtained from the AntConc application found the frequency of hedges and boosters in scientific articles. The results of this study showed that the use of modal verb hedges in the first position was 214 frequencies, followed by 59 adverbs of hedges, and verb hedges were 3 frequencies, while the use of booster in the first position was 202 frequencies, followed by adverbs booster of 63 frequencies, and booster verbs of 6 frequencies. This study shows that students ability to tendency to (1) use epistemic modalities in modal verbs, (2) tend to use more capital verbs that mean certainty and possibility, and (3) tend to use adverbs to mean epistemic modalities.
Traducción literal vs. traducción por defecto. Un desafío para los dos constructos mediante la traducción del egipcio clásico como caso extremo

This paper presents the results of a study that compares the constructs of literal translation (Schaeffer &amp; Carl, 2014) and default translation (Halverson, 2019) by means of an observational, exploratory study with Middle Egyptian translation as an extreme case in point. Two MA students in Egyptology at Universitat Autònoma de Barcelona and three recent graduates of the same MA programme took part in the study. They translated two excerpts from two Middle Egyptian literary texts into Spanish. InputLog was used to collect translation-process data and derive word-level indicators of cognitive effort from them: typos per word, word typing speed, and within-word pause. Results showed a clear link between default translations and cognitive effort (low number of typos, low number of respites, and fast writing speed). However, the assumption that deviations from literality cause greater cognitive effort was not observed. Hence, default translation may serve as a more adequate construct to describe the regular way translators perform.
Run-Time Prevention of Software Integration Failures of Machine Learning APIs

Due to the under-specified interfaces, developers face challenges in correctly integrating machine learning (ML) APIs in software. Even when the ML API and the software are well designed on their own, the resulting application misbehaves when the API output is incompatible with the software. It is desirable to have an adapter that converts ML API output at runtime to better fit the software need and prevent integration failures. In this paper, we conduct an empirical study to understand ML API integration problems in real-world applications. Guided by this study, we present SmartGear, a tool that automatically detects and converts mismatching or incorrect ML API output at run time, serving as a middle layer between ML API and software. Our evaluation on a variety of open-source applications shows that SmartGear detects 70% incompatible API outputs and prevents 67% potential integration failures, outperforming alternative solutions.
Designing a Student Performance Monitoring Dashboard Application Using the MVC Method and the Spring Boot Framework at Media Nusantara Citra University

The student academic performance monitoring dashboard is an application used by lecturers at the Faculty of Business and Education, Media Nusantara Citra University to digitally monitor student performance. The monitoring process currently carried out is still manual, which involves both data searching and manual file searching. Apart from that, this data can only be accessed by the academic department and lecturers must make a request first. On the other hand, the large amount of work and busyness of lecturers means that lecturers do not have much time in the process of collecting data for monitoring, while the monitoring process is very important for lecturers to know the progress and results of the learning process of the lecturers' students. Model, View, Controller (MVC) is an application development architecture that emphasizes 3 important components. These three components each have a focus of attention, responsibility and logic so as to speed up performance. For this reason, to solve the problem of monitoring student academic performance, a dashboard application was built using the MVC method. This monitoring dashboard application was built using the Java programming language with the Spring boot framework and is web-based. Spring boot is a framework for the Java programming language which is equipped with a Tomcat server, Annotation technology, and Maven as a Build Manager. With this application, it is hoped that it will make it easier for lecturers to carry out the monitoring process so that the monitoring process can be carried out anytime and anywhere. The output targeted in this research is a Student Academic Performance Monitoring Dashboard application. This research has a Technology Readiness Level (TKT) at level 2 which is expected to be useful for lecturers at Media Nusantara Citra University. This research also targets additional output, namely publication in a national journal indexed at least SINTA 4 with a target publication in November 2023.
A Study on the Improvement of Security Image Analysis Capability Using Artificial Intelligence

The mining of patient data in the health care industry is becoming an increasingly important field because of the direct effect it has on the lives of patients. In the field of medicine, one use of data mining is the early diagnosis of medical diagnostic conditions. However, extracting information from medical records is a laborious process that involves a lot of time and effort. Communities that are dominated by females have an elevated risk of developing breast cancer. Even though mammography is one of the most common ways to use computer-assisted diagnostics, there is still a chance that breast cancer will not be found even if it is one of the most common ways to find and screen for the disease. This indicates that just thirty percent of breast cancers are diagnosed at the appropriate time. Digital image pre-processing includes grayscale-to-binary conversion, noise reduction, and character separation. Most picture recognition algorithms employ statistical, syntactic, and template matching. Neural networks and support vector machines have enabled recent photo identification advances. This article discusses the second stage of the pre-processing procedure, which is adding a filter to the image after it has been segmented in order to make it seem more appealing. It works to identify the area of interest and improve the image by removing the breast border in order to apply filtering algorithms. The breast image's edge is reconstructed using morphological processes in the segmentation method that has been proposed, and breast masses are found by subtracting the two images. In addition, a modified bi-level histogram and homomorphic filters were used in order to improve the image's quality by reducing noise and enhancing contrast.
Cloud Computing Technology: An Effective Tool for Curriculum Delivery in Nigeria Educational Process

The paper examined Cloud Computing Technology: An Effective Tool for Curriculum Delivery in Nigeria Educational Process. This is because the current technology is a paradigm shift towards making the whole process of teaching and learning students’ centre thereby ensuring the development of the needed skills in this 21st Century that include, critical thinking, collaborations and problem solving. Notable to all, majority of students and teachers have one form of technology or the other, such as cell phones, mobile phones and mini-computers which makes it easy to access the internet at their fingertips. With this development, Teaching-Learning and Research in Education will undergone a phenomenal change which would makes the whole process changing so significantly. Hence, the use of these tools in the education sector will strengthen further and reform the system. Because it would enables learning everywhere and all the time. Based on the above, the paper explored the definitions and meaning of cloud computing; Implementation &amp; Use of the tools for Teaching and Learning, were discussed. Similarly, the components structure and its types was identified and explained such as: Public Cloud, Private Clouds and Hybrid Clouds The paper equally, identified Advantages as well as dis-advantages of the use of cloud computing in education. Such advantages include Accessible educational tools; Improved collaboration &amp; Better learning facilities. Lastly, conclusion and recommendations for the improved use of cloud computing in education were highlighted and this include, Educators considering implementing of the cloud into their context for teaching and learning should ensure that the tools can be effectively handle both by the students and teachers in order to achieve the curriculum objectives.
Arie Rip, <i>Nanotechnology and Its Governance</i> London: Routledge, 2019. Pp. 158. ISBN 978-1-1386-1053-8. £130.00 (hardback).

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Aplikasi Model ARIMAX dengan Efek Variasi Kalender untuk Peramalan Trend Pencarian Kata Kunci “Zalora” pada Data Google Trends

ARIMAX is a method in time series analysis that is used to model an event by adding exogenous variables as additional information. Currently, the ARIMAX model can be applied to time series data that has calendar variation effects. In short, calendar variations occur due to changes in the composition of the calendar. The purpose of this study is to apply the ARIMAX model with the effects of calendar variations to forecast search trends for the keyword "Zalora". Data were collected starting from January 2018 to November 2022 in the form of a weekly series. Based on the results of the analysis, the ARIMAX model is obtained with calendar variation effects with ARIMA residuals (1,1,1). Forecasting accuracy using the Mean Absolute Percentage Error (MAPE) of 10.47%. Forecasting results for the next 24 periods tend to fluctuate and it is estimated that in April 2023 there will be an increase in search trends for the keyword "Zalora".