Reviewerly/exHarmony huggingface dataset:
Unification of Modal Logic via Topological Categories

In this paper we provide a unifying description of different types of semantics of modal logic found in the literature via the framework of topological categories. In the style of categorical logic, we establish an exact correspondence between various syntactic extensions of modal logic on one hand, including modal dependence, group agent structures, and logical dynamic, and semantic structures in topological categories on the other hand. This framework provides us a uniform treatment of interpreting these syntactic extensions in all different types of semantics of modal logic, and it deepens our conceptual understanding of the abstract structure of modal logic.
Privacy Aspects of Contact Tracing Applications in Europe and Recommendations for Their Future Use

The first global pandemic in the age of digitalism indicated that there might be new types of privacy risks stemming from the processing activities taking place within the scope of digital contact tracing activities. While the right to life of all individuals living in the community should be primarily protected, their right to privacy should also be considered. Therefore, a balance between privacy and public health should be struck by both regulators and data controllers. The purpose of this review is to analyze the compliance efforts of data controllers in Europe with the existing EU data protection regulations, and guidance, and draw lessons for the use of contact tracing applications within the scope of potential disaster scenarios that may arise in the future by reviewing the existing literature and the privacy policies of the applications.
Intelligent Health Referral Model using Hybrid Recommender System

A health referral model using hybrid recommender system is a research work that will help build an effective information management for patient and doctors.The involvement of information technology is essential to guide people to find a Specialist (doctor) with whom they can build trust and confidence to discus personnel health issues with and medical treatment within locality.The increase in sickness and diseases has left several people helpless with no one to give a good suggestion on where to go and who to meet for solution and this has made Patients to sort for specialist Doctors in wrong places and hospitals, which has cost several patients a waste of time, money, and even loss of life.Hybrid recommender was applied .Hybrid recommender apply techniques that can filter information and narrow that information down based on user preferences or user needs and help users choose what information is relevant The methodology adapted was Object Oriented Analysis, Prototype Design Specification and Unified modeling language as the design tool.In this project, we developed a Doctors-to-Patients Recommender system using a hybridized algorithm.The referral process is done based on doctor specialization.The doctor have to enter is profit including the current place of work and pass achievement, the system will use it to automatically referral a patient that have that illness to that specialist.The Content-based filtering and Success Credibility Score model to ensure credible recommendations of Doctors to Patients.the implemented was done with hyper preprocessing language, JavaScript, Json and hyper text make-up language with the Apache web server to manage the Database developed using MySql.In the system 50 patient visit the site and the system was able to referral 46 to a specialist at different time interval.The result of the system has prove that hybrid recommender model is accurate and credible to referral patient to Specialist Doctors and the result shows that Patients can effectively be guided on the choice of specialist for consultations.In deduction, this study offers tools for assessing the performance of patient to doctor activity which are useful for both hospital management and healthcare administration
Practical Applications of Cryptocurrency Momentum and Reversal

In <ext-link><bold><italic>Cryptocurrency Momentum and Reversal</italic></bold></ext-link> from the Summer 2023 issue of <bold><italic>The Journal of Alternative Investments</italic></bold>, <bold>Victoria Dobrynskaya</bold> of <bold>HSE University</bold> in Moscow finds that cryptocurrencies display a momentum effect over short time horizons of two to four weeks and a reversal effect over long time horizons. Returns from capturing those effects are statistically significant and not tied to other cryptocurrency risk factors. In a comprehensive study of hundreds of strategies with varying sorting and holding periods, utilizing virtually all available cryptocurrencies, Dobrynskaya is the first to look at holding periods beyond one month for these strategies in the cryptocurrency market. She uses a winner-minus-loser (WML) portfolio approach to make her initial findings but also looks at winners and losers separately, multifactor alphas, and upside and downside betas. One important finding is that the loser side drives the WML portfolio performance. She finds significant alphas for short-horizon momentum strategies and long-horizon reversal strategies, and upside betas are significantly negative, particularly at longer horizons. Her results provide clarity to some of the contradictory results of past research on these effects in the relatively new asset class of cryptocurrencies.
Analisis Penggunaan Learning Management System Moodle dan Google Classroom dalam Meningkatkan Motivasi Belajar Mahasiswa

Data collection was carried out by providing research instruments through a questionnaire consisting of 25 statements. The questionnaire was then distributed to 36 students of Informatics Education Study Program, Citra Bangsa University. The results showed that 72.31 % of students are interested in learning by using Google Classroom. Conversely, 85.89% of students prefer to study using the UCB learning management system (LMS) rather than learn using Google Classroom. LMS UCB has the advantage of being able to provide students with learning material, quizzes, and exercises. Besides that, students can do assignments directly in LMS, and lecturers can process grades well. Thus, LMS is more recommended than using Google Classroom.
IMPLEMENTASI METODE SCRUM PADA WEBSITE PENDAFTARAN PASIEN RAWAT JALAN

Websites in health services are expected to be able to manage information and data processing to be faster and according to minimum service standards. This study aims to develop an outpatient registration website by applying the Scrum system development method. The research method used is descriptive research including data collection and software requirements analysis, website modeling and website development using the Scrum model. The website is developed using PHP and Mysql. This research was able to produce an outpatient registration website, the scrum method was able to make website work more effective, efficient and structured.
PERAN PENDIDIKAN KEAKSARAAN FUNGSIONAL BAGI MASYARAKAT BUTA AKSARA

Literacy education is a form of non-formal education services for illiterate citizens to learn to read, write, and count. Literacy Education consists of Basic Literacy Education and Advanced Literacy Education. Literacy Education is an educational service for Latin illiterate citizens so that they have the ability to read, write, count, speak Indonesian, and analyze so as to provide opportunities for self-actualization of potential. (Permendikbud RI No. 45 of 2015 Chapter 1 Article 1). The formulation of the problem to be discussed is that many people in Indonesia are illiterate. Illiteracy can be referred to as the inability of a person to use language and use it to understand a text, listen to words, express or express it in written and spoken form. The method used is the method of literature study. Collecting data cited from various sources such as articles. Or it can also be called the Traditional Review method, which means literature review. This method depends on the knowledge and experience of the researcher. The results of the review can be concluded that in non-formal education, it always provides various access needs for the community with various programs, one of which is literacy education which is very useful for reducing illiteracy in both early and old age.
PEMBERDAYAAN PEREMPUAN MELALUI PELATIHAN KECANTIKAN TATA RIAS WAJAH

Make-up, or what we often know, namely make-up, is done by women or women as a form of business to beautify themselves in order to make their appearance more attractive. The purpose of this cosmetology beauty training activity is so that women or women, especially housewives, can improve facial cosmetology techniques. This training is carried out by presenting tutors and models to make up as examples for the trainees. After that, the participants practiced the makeup on the models that had been prepared. The enthusiasm of the training participants was evident from the many questions asked about cosmetics that were good for various types of facial skin. Most of the participants already knew some of the makeup techniques.
PENGARUH METODE SAS BERBANTUAN MEDIA GAMBAR TERHADAP KEMAMPUAN MEMBACA DAN MENULIS PERMULAAN SISWA KELAS I SD NEGERI 1 TAMBLANG

This study aims to analyze the effect of applying the synthetic structural analytic method (SAS) using image media on the reading and writing abilities of first grade students in elementary school using a quantitative approach. Quasi-experimental research design with a non-equivalent pretest posttest model. The study population was all students of class I SD Negeri 1 Tamblang, North Toraja Regency, totaling 59 students, divided into two study groups with each class IA, namely 29 students, while class IB consisted of 30 students. The sampling technique used the cluster random sampling technique and class IA as the experimental class while class IB as the control class. The data collection technique is using a performance test for writing and a preliminary reading test. based on the comparative analysis of the average reading ability at the beginning of the experimental class and the control class, the value of t = 7.495&gt; 1.69726 and sig. (2-tailed) = 0.001.69726 and sig. (2-tailed) = 0.00 &lt;0.05 this shows that the SAS method has a significant effect on the initial writing ability of class I students of SD Negeri 1 Tamblang
PENGEMBANGAN MEDIA PAPIMAG (PAPAN PINTAR MAGNETIK) PADA MATERI SIMBOL RAMBU LALU LINTAS KELAS 3 SEKOLAH DASAR

This study aims to describe the development process and quality of papimag media on the material of symbols and traffic sign symbols for grade 3 elementary school students. The research is the ADDIE (The initial stage of analysis is performance analysis that can be done to find out the problems that are being faced in the classroom. Design designing or compiling a media creation framework from media design, material. Development develops learning media based on the initial design. Implementation conducts media trials in the learning process. Evaluation at this stage a final revision of the developed media is carried out). The subjects in this study were students of grade 3 UPT SD Negeri 131 Gresik, totaling 18 students. The learning model used during implementation uses 3 models, the first is Teams Group Tournament, Inquiry Based Learning, and Group Discussion. Data collection techniques in this study were using validation sheets and student questionnaires. Analysis of the data obtained from the validation sheet of the media expert in the graphic aspect obtained a percentage of 90% and the linguistic aspect obtained a percentage of 91.6%, while the validation of the material expert on the presentation aspect obtained a percentage of 75% and the content feasibility aspect obtained a percentage of 100% with the criteria of "very good".
IMPLEMENTATION OF THE ICE-BREAKING METHOD TO INCREASE FOURTH-GRADE STUDENT UNDERSTANDING OF THE MATERIAL “TELLING TIME” IN AL – A’RAF BILINGUAL ELEMENTARY SCHOOL

Ice Breaking is a learning method that can change the atmosphere from being less focused, boring, and boring to being fun and interesting. So that students concentrate on the teaching and learning process. This study aims to determine the application of the Ice breaking method can improve students' understanding of English subjects in telling material in fourth grade at Bilingual Al – A’raf elementary school. The design of this study uses a true experimental design technique using purposive random sampling. One class is the control class and the other is the experimental class. By giving a pretest and posttest. The sample in the study was 26 Bilingual Al – Al – A’raf Elementary School students. implementation research in the even semester of the 2022/2023 academic year. The results of the study show that the application of the Ice breaking method can increase the understanding of Tagged students with the results of the analysis of sig.0.02 &lt;0.05. This means that H0 is rejected and H1 is accepted. There was an increase between the pretest and post-test scores in the experimental class, namely, the results of pretest score of 84.69 while the post-test obtained an average score of 91.07. Thus the research hypothesis is accepted. It can be concluded that the application of ice-breaking has a significant and significant effect on students' understanding of learning.
Geofacets

Geofacets is a unique database for environmental researchers which draws, represents, organizes, and makes searchable information and data sets from various scientific resources through a single interface. Geofacets is both a research database and a comprehensive business solution that helps organizations maximize their time, energy, financial assets, and human resources. Geofacets draws its data from essential geoscience publications such as The Journal of Geochemical Exploration , Chemical Geology , The International Journal of Greenhouse Gas Control , The Journal of Structural Geology , The Journal of Volcanology and Geothermal Research , Sedimentary Geology , Geoscience Frontiers , Marine Geology , Global and Planetary Change , and Earth Science Reviews. Geofacets has positioned itself as the go-to resource for reliable information and data drawn from the interdisciplinary field of academic geoscience as well as from private industry.
Entanglement transmitted over 50 km

A new experiment incorporates all the essential building blocks of a long-distance quantum network, as Martijn Boerkamp explains.
Kajian Etnososiologi Jawa pada Sastra Anak di Antologi Anak “Meong Lan Arimong"

Children's literature will be the main attraction for children to learn about their culture. This study aims to describe: (1) socio-cultural relations; (2) the process of learning culture includes internalization, socialization, and enculturation contained in the anthology of children's stories "Meong lan Arimong". This research is classified as qualitative research with a qualitative descriptive method. The contents of children's stories are discussed using Javanese ethnosociology in the form of social and cultural relations of Javanese families and the process of learning one's own culture. The data used in this research are words, phrases, sentences, and discourses that contain socio-cultural relations, the process of learning culture itself includes internalization, socialization, and enculturation. The data source used is an anthology of children's stories “Meong lan Arimong. The research subjects were taken using purposive sampling. The data collection technique uses document analysis techniques, while the data analysis techniques use interactive analysis techniques. Based on the results of the analysis that has been carried out on the seven selected Jaya Baya magazine crikaks, all of them have: (1) socio-cultural relations caused by the existence of Javanese culture which is raised in each children's story; (2) the process of learning culture itself includes internalization, socialization, and enculturation experienced by the main character and the most prominent socialization process is obtained because it is in that process that reciprocal interactions occur.&#x0D; Keywords: ethnosociology; childrens stories; children's literature; meong lan arimon
Sentiment Analysis of Tweets About Allowing Outdoor Mask Wear Using Naïve Bayes and TextBlob

Covid-19, a virus that attacks the respiratory tract and has a fairly high mortality rate, has spread throughout the country. On March 11, 2020, WHO declared Covid-19 a global pandemic. The government is trying various efforts to reduce the number of sufferers of this virus. Starting from the implementation of the lockdown, PPKM, to making Government Regulations related to the use of masks and so on for personal protection. In June 2021, there was a spike in Covid-19 cases in Indonesia and Covid-19 patients increased drastically. Conditions at that time were very chaotic, and left trauma for some people. On May 17, 2022, the government made concessions in the use of masks in open spaces while maintaining social distance. Even though masks play an important role in preventing the spread of the virus. With this, a research related to "Analysis of Sentiment on Tweets regarding Allowance for the Use of Masks in Outdoors using Naive Bayes was carried out" to find out public opinion. The research was conducted using Text Mining through Twitter sentiment and Naive Bayes for classification. Based on research, the majority of twitter users give a neutral response. This is indicated by the number of neutral sentiments of 75.76% or about 757 tweets. The data used in this study, namely 1000 Indonesian tweets with the keyword 'jokowi mask'. Testing data of 20% resulted in a more accurate model, which resulted in an accuracy of about 85%, while the model using testing data of 30% only produced an accuracy of about 83%.
Feature Selection in Naïve Bayes for Predicting ICU Needs of COVID-19 Patients

COVID-19 is a global pandemic that requires a coordinated global response in all healthcare and national healthcare systems. Identifying patients at high risk of contracting the COVID-19 virus is crucial to increasing awareness before patients become further infected by the virus, which can cause severe respiratory illnesses requiring specialized care in intensive care units (ICUs). This study aims to predict the need for ICUs in patients infected with the COVID-19 virus. The predicted ICU requirements serve as a reference for hospitals to meet the ICU needs of COVID-19 patients. The prediction of ICU requirements for COVID-19 patients is performed using the Naïve Bayes algorithm, and particle swarm optimization (PSO) used to obtain the best accuracy values from Naïve Bayes. In the initial testing, Naïve Bayes without feature selection resulted in an accuracy rate of 74.75%. Testing Naïve Bayes+PSO by increasing the number of PSO generations shows that as the number of generations in PSO increases, the accuracy rate also increases. Testing Naïve Bayes+PSO with 3000 generations and a population size of 20 shows an increase in the accuracy rate to 80.95%. Testing Naïve Bayes+PSO by increasing the population size to 40 with 1000 generations for each population size shows an increase in the accuracy rate to 80.70%.
Performance Analysis and Development of QnA Chatbot Model Using LSTM in Answering Questions

This research aims to evaluate the performance of a Long Short-Term Memory (LSTM) based chatbot in answering questions (QnA). LSTM is a type of Recurrent Neural Network (RNN) architecture specifically designed to overcome vanishing gradient problems and can store long-term information. The method used is 5-fold cross-validation to train the chatbot model with 15 epochs at each fold using the dataset provided. The results showed variations in model performance at each fold. At the 5th fold, there was a decrease in performance with 84.63% accuracy, 96.36% precision, 64.9% recall, and 69.84% loss value. This finding shows that there is variability in the performance of the QnA chatbot model at each fold. In conclusion, the LSTM chatbot model can provide good answers with high accuracy and precision. Still, performance variations need to be considered in the use of this chatbot.
Next Word Prediction for Book Title Search Using Bi-LSTM Algorithm

Finding a suitable book title is still quite difficult at the moment. We often guess what book title we want, but in reality the book title is often not available. This research aims to overcome these problems by producing an accurate and efficient prediction model in predicting the next words in book title search using a deep learning algorithm, namely Bidirectional Long Short Term Memory (Bi-LSTM). The research stages consist of data collection, data preprocessing, data modeling, evaluation, and implementation. This research uses a dataset of Indonesian book titles obtained from the bukukita.com online bookstore website with 5618 data. The results show that the resulting deep learning model can predict the next words in the book title search with an accuracy of 81.82%. The model is implemented in the form of a web application using the Django framework, Python language, and MySQL database.
Goal-Oriented Modeling of an Urban Subway Control System Using KAOS

The extent to which a safety-critical system, such as an urban subway control system, accomplishes its goals is a fundamental metric of its success. Identifying and assessing these goals should thus be one of the primary tasks in safety-critical system development. The breakdown of these systems may result in the loss of human lives and assets. The failure of these systems is caused by insufficient, incomplete, ambiguous, or conflicting requirements. Non-functional requirements are also separated from requirement specifications. Goal-oriented requirements engineering methodologies, such as KAOS, are used to tackle these challenges by providing adequate, complete, unambiguous, and consistent requirements in terms of goals. As a result, the KAOS approach is utilized in this article to construct a goal-oriented model of an urban subway control system. Variability and obstacle concerns are also addressed in this study.
Geo-Informatics for the Future: A Systematic Literature Review on the Role of WebGIS in Infrastructure Planning and Development

The crucial role of geographic information in contemporary transportation infrastructure planning underscores the need for efficient and practical tools. This systematic literature review aims to provide a comprehensive overview of the current evidence concerning Web Geographic Information Systems (WebGIS) application in infrastructure planning. It further identifies potential avenues for future research.&#x0D; The study leverages digital libraries to source peer-reviewed papers and published journals, evaluating the characteristics and applications of WebGIS. The review offers an in-depth analysis of WebGIS implementation, focusing on flexibility, location, utilized sectors, and environmental impacts.&#x0D; The methodology involves identifying research topics, developing a search plan, and selecting relevant articles using rigorous search techniques. The selected articles undergo a thorough quality assessment before data extraction. This review seeks to answer key research questions: How does WebGIS aid infrastructure management in agricultural settings? Can WebGIS be implemented free of charge? Is it flexible and user-friendly? Can WebGIS address the issue of declining seawater quality? Has WebGIS been successfully implemented for infrastructure planning globally?&#x0D; This review aims to shed light on the potential of WebGIS in shaping future infrastructure planning and to encourage further exploration in this field.