Reviewerly/exHarmony huggingface dataset:
Barriers to Using Mobile Devices in the Classroom

Mobile devices in specific, cell phones have become progressively trendy. Even though the usage of mobile devices can accelerate the learning process, there may be obstacles to utilizing it for learning purposes. This study directed to recognize and examine the barriers and catalysts of using mobile devices as an educational device from the perspective of educators. The numerous barriers impeding the effective integration of mobile devices in the classroom have been identified. This study has uncovered several key findings that shed light on the challenges hindering the effective integration of mobile devices in the classroom.
A deep learning model to triage and predict adenocarcinoma on pancreas cytology whole slide imaging

Abstract Pancreatic fine-needle aspirations are the gold-standard diagnostic procedure for the evaluation of pancreatic ductal adenocarcinoma. A suspicion for malignancy can escalate towards chemotherapy followed by a major surgery and therefore is a high-stakes task for the pathologist. In this paper, we propose a deep learning framework, MIPCL, that can serve as a helpful screening tool, predicting the presence or absence of cancer. We also reproduce two deep learning models that have found success in surgical pathology for our cytopathology study. Our MIPCL significantly improves over both models across all evaluated metrics (F1-Score: 87.97% vs 88.70% vs 91.07%; AUROC: 0.9159 vs. 0.9051 vs 0.9435). Additionally, our model is able to recover the most contributing regions on the slide for the final prediction. We also present a dataset curation strategy that increases the number of training examples from an existing dataset, thereby reducing the resource burden tied to collecting and scanning additional cases.
Mu-Net a Light Architecture for Small Dataset Segmentation of Brain Organoid Bright-Field Images

To characterize the growth of brain organoids (BOs), cultures that replicate some early physiological or pathological developments of the human brain are usually manually extracted. Due to their novelty, only small datasets of these images are available, but segmenting the organoid shape automatically with deep learning (DL) tools requires a larger number of images. Light U-Net segmentation architectures, which reduce the training time while increasing the sensitivity under small input datasets, have recently emerged. We further reduce the U-Net architecture and compare the proposed architecture (MU-Net) with U-Net and UNet-Mini on bright-field images of BOs using several data augmentation strategies. In each case, we perform leave-one-out cross-validation on 40 original and 40 synthesized images with an optimized adversarial autoencoder (AAE) or on 40 transformed images. The best results are achieved with U-Net segmentation trained on optimized augmentation. However, our novel method, MU-Net, is more robust: it achieves nearly as accurate segmentation results regardless of the dataset used for training (various AAEs or a transformation augmentation). In this study, we confirm that small datasets of BOs can be segmented with a light U-Net method almost as accurately as with the original method.
ANALISIS EFEKTIVITAS INSTALASI PENGOLAHAN AIR LIMBAH (IPAL) DI RUMAH SAKIT UMUM DAERAH KABUPATEN SUMEDANG DENGAN PARAMETER BOD, COD DAN TSS

Sumedang regional general hospital in the implementation of activities produces liquid waste which is if disposed directly to environment will cause water contamination and human health problems. The purpose of this study is to analyze the effectiveness of waste water treament plant performance in treating waste water based parameters BOD5, COD and TSS. The analysis of this study uses a T-Test statistical with SPSS software and also by calculating the efficiency of pollutants removal with using data before and after treatment to determine the effectiveness of waste water treament plant. Based on laboratory test result, the effluent concentration for BOD5, COD and TSS have fulfilled the standard discharge limit according to Ministry Of Environment and Forestry no.68/2016 and the chrom content in waste sludge has fulfilled with the standard discharge limit according to Ministry Of Environment and Forestry no.05/2014. The T-test interpretation result showed that the BOD5 and COD parameters have significant difference between the data before treatment and after treatment. Based on laboratory test result in November 2020, the efficiency of removal pollutanst for TSS 94.59%, BOD5 78.78% and COD 73.23%.
Upaya Meningkatkan Prestasi Belajar Akuntansi Melalui Metode Pembelajaran Tutor Sebaya Pada Siswa Kelas XI Ak.2 SMK St. Willibrodus Betun Tahun Pelajaran 2022/2023

The purpose of this study was to improve student achievement in class XI AK.2 SMK St. Willibrodus Betun in Accounting subject through the application of peer tutoring learning methods. The problems faced are the lack of student interest in accounting subjects, and the difficulty of maintaining focus during class. This has a negative impact on their academic performance. The proposed solution involves utilizing the peer tutoring method, whereby students receive assistance from their classmates in understanding accounting concepts. The research was conducted using the Classroom Action Research (CAR) method and involved 20 students as research subjects. The results showed that there was a significant increase in student achievement after the application of the peer tutoring method. In cycle I, 13 students successfully completed their studies with an average formative test score of 74.50 and a percentage of learning completeness of 65.00. In cycle II there was an increase in the number of students who completed their studies, with a total of 18 students. The average score of formative tests also increased to 88.00, and the percentage of complete learning reached 90.00. The conclusion drawn is that peer tutoring is an effective learning method in improving the academic achievement of Accounting students.
Weak Kleene and Other Weak Logics of Conditionals

This paper presents a weak Kleene approach to conditionals that preserves some salient formal features of conditionals, particularly their interdefinability with Boolean logical connectives. I argue that such an approach fares better than other proposed weak logics of conditionals in this regard. In particular, it fares better than the logics proposed by Cooper, Cantwell, Farrell, De Finetti, Égré, Rossi, and Sprenger.
Rancang Bangun Lingkungan Pemrograman Python Dengan Metode Chatbot Pada Platform Whatsapp

Chatbot advances have been widely adopted by various companies as support for customer service. Chatbot itself is a technology that simulates or imitates human-like conversations via text messages. Basically, the development of the Chatbot system in this research aims to make it easier for users if they want to learn programming in the Python programming language. Although a web-based application is available for this purpose, namely Google Colab, this web application interface is difficult to use when programming on the small screen found on a mobile device. With this problem as a background, the author built a chatbot system that can help users carry out Python programming via WhatsApp. Execution of program code sent via WhatsApp is implemented by utilizing the Python programming language feature to execute program code in string form. Apart from that, the author provides a program code management feature for many users, so that this Chatbot system can be used by many users at once.
Development of AI-Enabled Contactless Visitor Access Monitoring System

This research focuses on developing an AI-enabled Contactless Visitors Access Monitoring System. The monitoring system integrated a facial recognition system with a real-time database. Visitors registered themselves through an online registration form. This research developed and compared two different facial recognition systems. The first facial recognition system integrated the dlib model with the face recognition library, while the second integrated the FaceNet model with the Haar Cascade Classifier. Twenty facial images were collected. The researcher found out that the facial recognition system with FaceNet has higher accuracy of 82% while the has 76% of accuracy. The value of EER obtained for FaceNet is at 51% with an allowed threshold of 0.52. This research found that the accuracy of the facial recognition system could be affected by different conditions, such as the visitors’ facial features, the distance between the camera and the face, and the illumination condition of the test environment. The number of images does not affect the speed and the accuracy of the facial recognition system in this research due to the small number of images.
RFID and Facemask Detector Attendance Monitoring System

The article emphasizes the significance of attendance monitoring for safety during the COVID-19 pandemic and proposes an RFID-based solution coupled with face mask detection systems to address attendance challenges. The project aims to create a contactless monitoring system that ensures face mask compliance and provides real-time attendance data for data-driven decision-making. The article also covers various technology-related topics, including the historical usage of face masks, the development of attendance systems using biometric identification and electronic methods, and facial recognition technology's applications in surveillance and finance. It introduces XAMPP, a user-friendly web application development and testing tool, and presents an overview of the IC7408 chip used in digital electronics. The study's key findings show that increasing sample size and optimizing epochs and batch size improve face mask detection accuracy, while RFID scanner distance affects scanning delay and accuracy. The research provides valuable insights into the performance of the proposed attendance monitoring system.
Sosialisasi dan Pendampingan Pembelajaran Berbasis Video dengan Aplikasi ‘Screen O-Matic’ Bagi Guru Sekolah Dasar Kartika IV-6 Malang

The aim of the activity is providing socialization and video-based learning assistance with "Screen O-Matic" application for teachers at SD Kartika IV-6 Malang. The agenda is presented in three stages, namely preparation, implementation, and evaluation. By implementing this stages, the teachers can develop online-based learning models and media using a variety of applications, including using the "Screen O-Matic" video application. The output targets achieved through this Community Service activity include: 1) increasing knowledge about video-based learning models and media for teaching at SD Kartika IV-6 Malang; 2) increasing learning innovation by developing video-based applications "Screen O-Matic".In conclusion by using "Screen O-Matic" video application, teaching learning process can be delivered in joyful learning, creative and innovative. Digital Literate is a must for Nowdays teachers.
Sistem Pakar Diagnosa Hama Penyakit Tanaman Jambu Kristal Penerapan Metode Certainty Factor

A guava variety called Jambu Kristal (Crystal Guava) that shows potential to be developed in Indonesia because it is suitable for soil, climate, and weather conditions in Indonesia, as well as increasing market demand. Nevertheless, crystal guava plants remain vulnerable to pests and diseases that can hinder growth and cause losses to farmers. If pest and disease attacks on crystal guava plants are not diagnosed and treated immediately, the consequences can include plant death, damage to the fruit, as well as a significant decrease in production. This research develops an expert system application that aims to assist farmers in diagnosing pests and diseases in Crystal Guava plants. In this research, the Certainty Factor Method is used as a reasoning tool to estimate the level of confidence in diagnosing pests and diseases that attack crystal guava plants. The Certainty Factor algorithm processes the uncertainty value input from the user using a single premise and conclusion to produce a diagnosis value in the form of a percentage. The expert system is supported by 8 knowledge bases that contain information related to pests and diseases in Crystal Guava plants. The built expert system shows that the system is able to diagnose Root Rot Disease with a confidence value of 97.60%.
Penggunaan Support Vector Machine Untuk Analisis Sentimen Ulasan Aplikasi Truecaller Dan Getcontact

Spam calls are any calls made without the consent of the recipient and for any reason. These calls can originate from marketing, advertising, notifications, or fraud. The average Indonesian receives 14 spam calls per day. Only half of it comes from contact book numbers. According to the Google Play Store, the Truecaller and Getcontact apps offer a number of advantages as they each help identify callers and prevent spam. However, in this regard, spam call blocking software has a number of drawbacks, including identifying spam calls incorrectly and blocking useless calls. Sentiment analysis can help users choose applications that suit their needs and in this study intends to analyze reviews on the sentiments of the two applications namely Truecaller: Caller Id and Getcontact by analyzing effectiveness based on the application reviews Support Vector Machine classification algorithm which contains basic guidelines for maximizing hyperplane boundaries that separate the two datasets, are used in the classification process of this study. The results showed that the Truecaller application at 10-fold cross validation had an average accuracy of 88.20% and the Getcontact application had an average accuracy of 87.90%. Meanwhile, the sentiment aspect of the Truecaller application has an average accuracy value of 60.20%, while the Getcontact application has an average accuracy of 63.30%.
Pendampingan Siswa dalam Belajar Matematika Melalui Eksplorasi Bangun Datar dengan Seni Kreasi Origami

Combining art with learning math creates a unique and engaging experience for students. The creative art of origami is an interesting and creative way to learn and understand flat shapes. Origami is the art of folding paper into various geometric shapes with a certain precision and technique. Through origami, students can visualize and understand various geometric concepts such as symmetry, angles, and size ratios in a practical way. For example, they can fold paper into a triangle, square, or circle, and in doing so, observe the properties of each of these shapes. The purpose of this community service is to teach students flat shapes using origami paper media. The method used in carrying out community service is in the form of socialization, introduction and practicing playing while learning to build flat shapes using origami paper. Students can be seen from the enthusiasm during the activity and it appears that students understand the flat shape material.
The use of gamification in the process of learning a foreign language

The article considers the method of gamification in teaching a foreign language. Game mechanics and an example of using the gamification method in a German lesson are presented. It is concluded that the use of gamification helps to maintain motivation for the educational process.
Emergency remote teaching during the covid-19 pandemic: Experiences among Mexican university students

The aim of this research was to explore the experiences of emergency remote teaching (ERT) during the covid-19 pandemic among students at a public university in the northwest region of Mexico. A descriptive correlational exploratory cross-sectional study was conducted with a nonprobabilistic sample of 1550 students. A survey was designed and validated by experts, and it was implemented online using the Microsoft Forms platform. Findings revealed that more than half of the students demonstrated very good or excellent proficiency in virtual platforms. Additionally, 28% of women experienced a difficult or very difficult adaptation process to the platforms, while this percentage was lower among men (20.9%). Students expressed that the academic performance of their instructors during ERT ranged from average to good, but the majority indicated that instructors were not adequately prepared to conduct classes in this modality, since teaching through virtual platforms requires planning and designing strategies. Despite both teachers and students became familiar with digital tools during the pandemic, it is recommended to encourage synchronous digital environments for teachers and explore didactic strategies for asynchronous ones.
Developing Children’s Data Literacy through Navigating, Video-logging, and Making in a Library

Data literacy means the ability to understand, evaluate, collect, make, and use data for ethically appropriate purposes (Prado &amp; Marzal, 2013; Yoon &amp; Copeland, 2020). Despite its importance in the 21st century, data is often regarded as a difficult area that only some professional adults can deal with, and most children do not have enough opportunities to feel that their everyday life is indeed connected to data and find it interesting (Acker &amp; Bowler, 2018). To situate data in children’s own lives and the spaces they usually go to (Stornaiuolo, 2020), a design-based research project was conducted by designing and implementing an educational program for children and their families about data literacy in non-computational ways in a public library. Two main sessions (1.5-hour long each) and one optional making session included navigating the whole library space while video-logging with a GoPro camera and worksheets; creating their own creative data visualizations with drawing and making tools (e.g., color papers); making artifacts with maker technologies and brainstorming a metadata structure about the artifacts. Video data from GoPro cameras were collected and preliminary analysis was conducted. Findings show how children could make different observations of familiar objects (e.g., books, tables) in the library and turn their observation to the perspective of “data” and how different types of non-computational activities could align with children’s basic understanding of data.
Empathy, Confidence, and De-Escalation

This research analyzes the results of a study that is part of a larger, interdisciplinary, and multi-institutional project that examines the usability and effectiveness of VR training for library and information science (LIS) graduate students and professionals in gaining skills for interacting effectively with patrons in crisis. This paper reports on the findings related to the effectiveness of VR training for teaching empathy, confidence, and de-escalation skills for LIS graduate students. The findings illustrate that VR has the potential to impact LIS graduate education by reaching a wider audience that introduces training in low-stakes, immersive environments and that does not pose harm to patrons in crisis. This study also contributes innovative approaches that support training in skills including empathy, confidence, and de-escalation.
Impact of Social Media on Strategic Management in Morocco

Purpose: The study sought to analyze the impact of social media on strategic management in Morocco&#x0D; Methodology: The research was conducted entirely on desktop review method. Secondary data, or data that doesn't require actual observation in the field, are the focus of desk research. Because it requires little more than an executive's time, telephone rates, and directories, desk research is generally seen as a low-cost strategy in comparison to field research. As a result, the research used data that had already been collected and reported. This secondary data was readily available via the internet's digital library and scholarly articles.&#x0D; Findings: The results show that social media has had a profound impact on strategic management. It has enabled organizations to identify and capitalize on opportunities, manage risks, and increase efficiency. By leveraging the power of social media, organizations can gain valuable insights into their customers, competitors, and the market, enabling them to make more informed and effective decisions. Social media has become an increasingly important part of the business landscape and its impact on strategic management in Morocco has been profound.&#x0D; Unique Contribution to Theory, Practice and Policy: Future research in strategic management may be grounded in either the resource based view theory or the network based view theory. Policymakers, researchers, and academics from all across the world will all stand to gain from this study's findings. The study's findings will also be used by the country's top strategic management executives to boost the effectiveness of social media across all of their operations and initiatives. According to the research, social media organizations may boost their productivity in key areas by adopting rules for dealing with conflicts.
Motor Vehicle Insurance Anti-Fraud Dynamic System Based on Tripartite Evolutionary Game

Insurance fraud not only increases the burden on policyholders but may even affect the normal operation of insurance companies. Based on the assumption of bounded rationality, this article establishes the tripartite evolutionary game matrix for policyholders, insurance companies, and government departments. In this article, Gaussian white noise is introduced to simulate the random interference encountered by each subject in the evolutionary game, and the evolutionary stability strategy of the tripartite stochastic evolutionary game under different conditions is discussed. Considering the importance of fraud recognition rate, the recognition accuracy rate is introduced into the stochastic evolutionary game, and the necessity of introducing fraud recognition rate into the game is proved by simulation. In the context of society, we have joined the government supervision department into the game and realized the supervision mode of social co-governance by using the social public opinion to reward and punish the government reputation.
U-Net for nuclei image segmentation

The nucleus is the core of a cell. The genetic information, commonly known as a living being&apos;s DNA, is stored in this massive yet tiny membrane-bound organelle. Biomedical image segmentation has a lot of scope for improvement, thus it&apos;s been hypothesized that by segmenting high-resolution nuclei images, we can extract high-quality nuclei features. Deep Learning techniques are thought to have a bright future in computing pathology. However, in this case, we&apos;re leveraging U-Net to automate nucleus identification in order to help speed up the development of therapies for everything from rare disorders to the common cold.
Conceptualizing Slow Curation

The pressure to do things quickly is a constant in our professional lives as data curators. But what if we slowed down our work? Taking inspiration from the Slow Movement and its various sub-genres, we propose the idea of Slow Curation, specifically for the application of curating research data. Data curation is the process of reviewing datasets to prepare them for sharing, use, and reuse. We have identified areas where Slow can be embraced in the Data Curation Network’s CURATE(D) model. We also advocate for a few ways, outside of curation, where data curators can collaboratively advocate for Slowing down our work for the better. Join us as we practice radical self-care and advocate for our communities by embracing Slow and easing our way out of Busy culture.Positionality Statements:All authors are employed at large and wealthy doctoral granting institutions in the United States. Their identities and experiences have directly informed and influenced this piece.Joanna is a cisgender, white, heterosexual, able bodied female.&amp;nbsp;Wanda is a white gender non-conforming queer, able bodied person who is a first generation undergraduate and graduate college studentMikala is a cisgender, white, heterosexual, able bodied female.