Reviewerly/exHarmony huggingface dataset:
Sistem Kriptografi Klasik Dengan Memanfaatkan Orde Dari Grup Titik Pada Kurva Eliptik Bentuk Montgomery

Elliptic curve cryptography is one of the application fields of algebra and number theory concepts. One form of elliptic curve cryptography is Montgomery elliptic curve cryptography. In this paper, a method for a classical cryptographic system be formulated, consisting of encryption and decryption involving twenty-six alphabetical letters which are mapped to points on an elliptic curve by utilizing the order of the point group on the Montgomery elliptic curve. Several examples of implementation in simple cases are given to verify the results.
Development of Android-based Listening Practice Application (FunNy-Fun&amp;Handy) with Popular Culture Topic as An Innovative Learning Media

This research aims to develop an Android-based application as a learning medium for student exercises containing audio on popular cultures to practice their English listening skills. This research method used research and development with the ADDIE model, namely Analysis, Design, Development, Implementation, and Evaluation. Data was collected using a questionnaire for validators. A questionnaire was used to collect data for the application, material, and learning practitioner. In the development stage, the validators declare that this product was very valid and practical. It was shown that the scores given by the English lecturers were 91,4 and 90,4, and the Programmer validator gave it 94. Meanwhile, the average score collected from the practical sheet was 90. After the digital listening application was revised and evaluated, this product was stated as effective, showing that 4 students were in the B2-Upper Intermediate level, 12 students are in C1-Advance, 8 students were in C2-Proficient and no more students in the intermediate level. This app was appropriate for students to use as a platform to practice their listening skills outside the class.
THERAPY WITH MUSIC AND OTHER KINDS OF ART IN THE REHABILITATION OF DISABLED CHILDREN

Particular attention in that article is devoted to the review of research that studies the influence of arts therapy methods on the mental and physical health of children with disabilities in rehabilitation. Objective data are presented demonstrating the effectiveness of using such methods of treatment with music, fine arts, and dancing, in the rehabilitation practice of children with disabilities. The expediency of the formation of complex programs of rehabilitation treatment using arts therapy methods on a fundamental evidence-based basis is substantiated.
OA usage reporting: Understanding stakeholder needs and advancing trust through shared infrastructure

The complexity of usage reporting for Open Access (OA) content continues to grow, particularly with content syndication to organizations such as ScienceDirect and ResearchGate, which deliver content across multiple platforms at an unprecedented scale. What kind of usage data do diverse stakeholders (including libraries, publishers, authors, and editors) need? Can the work done to support OA book usage data analytics use cases inform OA article and data use cases? What standards and policies are required to ensure the usage data is accurate and meaningful? What infrastructure is needed to collect and disseminate this data effectively and efficiently? This paper brings together four different perspectives to consider these questions: an OA publisher, a research infrastructure, an emerging usage data trust, and a usage analytics service provider. The authors walk through what is known, and then start to unpack the questions for which they do not yet have answers. Their goal is to inform the community’s understanding of the challenges ahead and, hopefully, start to lay the groundwork for constructive policies and shared solutions.
Video quality assessment based on deep learning

This article proposes a no reference video quality assessment method based on deep learning, aiming to simulate human perception of video quality and evaluate videos. This method evaluates the quality of videos by learning effective feature representations in the spatiotemporal domain. First, in the spatial domain, 2D-CNN is used to extract the spatial quality of video frames. Then, in the temporal domain, Recurrent neural network (RNN) and pyramid feature aggregation (PFA) module are used to model the temporal domain and aggregate the frame level feature quality. The experiment shows that the method proposed in this paper has good performance on the KoNViD-1k and CVD2014 datasets, and also indicates that the method has high generalization ability.
Detection of rotating small targets in remote sensing images based on improved yolov5s

Aiming at the characteristics of clustering, multi-scale changes, low contrast, and complex background in remote sensing images, this paper proposes an improved rotation frame algorithm based on yolov5s network, which reduces the traditional horizontal detection frame in remote sensing images by rotating frames. Missing detection of small targets due to aggregation and rotation problems; by using the attention mechanism module CBAMC3 that combines space and channels in the Backbone part to replace the original C3 module, the feature representation ability of targets of different scales in remote sensing images is improved; In the loss function, the Focal Loss function is used to reduce the complex background of the remote sensing image and the certain influence of the imbalance of positive and negative samples, and strengthen the training weight of the positive samples; at the same time, the Copy Paste data enhancement is used to enrich the number of samples on the data set. Enhance the generalization ability of the model.The result on the DOTA dataset reaches map86.4%, which is 3.1% higher than the 83.3% of the original yolov5s, which proves that the model has high detection accuracy in remote sensing detection and has certain reference value for detecting images under remote sensing.
Evolutionary Learning Search Engine

Search engine algorithms work by taking the important elements of a web page which includes the title of the page, the content of the page, and keyword density. By using these key elements, search engines use their proprietary algorithms to come up with a ranking for each web page such that users can get most relevant results. Each search engine’s algorithm is unique, so a top ranking on Yahoo! does not guarantee a prominent ranking on Google, and vice versa. The aim of this study is to develop a search engine mainly for handling programming related queries based on Evolutionary Learning. This paper also focuses on feature snippet as an add on for displaying source code for relevant code search. The proposed system works on a plethora of domains including machine learning and big data analytics for improving the search results and refining them.
Debugging Presentation Patterns

In this chapter, you will look at another Python IDE, Jupyter Notebook and Lab, with a case study introducing a few more debugging analysis techniques and implementation patterns. Finally, after comparing Python CLIs and IDEs, you will discern a few basic debugging presentation patterns.
Application of The Simple Additive Weighting Method in Developing Employee Assessment Decision Support System in Marketplace Company Bukalapak

The purpose of this study is to investigate how managers, team leaders, and supervisors can evaluate top performers with the aid of simple additive weighting in decision support systems. In this study, interviews, observation, and related literature reviews were employed as data collection techniques. This system employs fuzzy simple additive weighted (FSAW) as its approach. Two techniques, AHP and WP, were used to develop the system. Rapid Application Development, or RAD, is the system development methodology employed in this study. The findings of the study led to the following deductions: The results of this application calculation do not directly determine when assessing the best employee; you must wait for a decision from the team leader, supervisor, manager or meeting. The results provided by the best employee assessment decision support system method can be implemented using dynamic or changeable criteria to determine the best alternative. There are seven criteria used for research on evaluating the best employees in this application, namely: average process. Processes include: quantity; quality; on time; and teamwork. Productivity, which includes days in and days out/holidays. These criteria are only a basis for research in writing about the best employees, but to add or subtract criteria, you can add or subtract them in the best employee assessment application system using SAW.
What AI and Machine Learning Can Do for Python Debugging

In this chapter, you will survey the possibilities of using the rapidly evolving AI/ML to aid, enhance, and even revolutionize the traditional manual Python debugging process.
Securing Laravel Applications

In the previous chapter, we delved into the crucial realm of advanced third-party integrations in Laravel, expanding the functionalities of our applications through seamless integration with payment gateways, social media platforms, email marketing services, cloud storage providers, and custom APIs. As we continue our exploration of Laravel's advanced features, we now shift our focus to an equally essential aspect—securing Laravel applications.
Technocracy and the Humanitarian Prospects of the Human Being Future

It is shown that modern reality dictates a change in the priorities of humanistic representatives of justice, compassion, sympathy, altruism, etc. to&nbsp;the more pragmatic values of technocracy. A comparative analysis of humanistic&nbsp;approaches to the future of man contained in the works of Academician I. T. Frolov&nbsp;(1929-1999) and technocratic thinking, technocratic culture was carried out. There&nbsp;is a priority in society of economic efficiency, management, technical achievements,&nbsp;substitutability, irresponsibility. Human is considered not as a person, but as an&nbsp;object of manipulation, as a component of the system. As an example of a technocratic&nbsp;approach, the program of the great reset of the world order by K. Schwab is&nbsp;analyzed. One of the reasons for the widespread use of technocratic approaches is&nbsp;the dehumanization of education. The reduction of the humanitarian component of&nbsp;higher education leads to a narrowing of the horizons of students, a simplification of&nbsp;their ideas about the world, culture and human. The necessity of the development by&nbsp;students of knowledge about a person, his place in the natural and social worlds, and&nbsp;interactions with technology is shown.
A Rapid Earthquake Disaster Assessment Platform Based on Cloud Computing

Abstract In the past few decades, earthquakes have been a major cause of casualties and economic losses. The rapid assessment system for earthquake disasters plays an important role in earthquake prevention, disaster reduction, and emergency command by calculating the economic losses and casualties caused by earthquakes in a relatively short time after the occurrence of an earthquake. Although there are now many rapid assessment systems for earthquake disasters, most of them adopt C/S and B/S architectures, which have limited computational efficiency during large-scale earthquakes. Based on these factors, this study aims to build a cloud computing-based rapid assessment system for earthquake disasters. The main modules of the system include intensity impact field calculation, building damage assessment, economic loss assessment, casualties assessment, and model parameter calibration. The results show that the system significantly speeds up the calculation process and shortens the assessment time. It can provide timely disaster assessment information to relevant departments in a short period and provide technical support for emergency decision-making.
Implementation of A Blood Donor Information System Using Mobile Applications Gunung Kidul District

Blood donation is a common charitable activity in many communities. Consequently, the Indonesian Red Cross (PMI) in the Gunung Kidul district frequently organizes such humanitarian events across various locations. However, not everyone is aware of these events or is able to participate in blood donation. The lack of information dissemination and blood donation events are significant factors contributing to the low community participation. The existing system for searching, processing, and creating data is still manual, which hinders the efficiency of administrative tasks. Addressing these issues, the aim of this research is to develop an Android-based blood donation information application. This initiative is particularly vital as the PMI in Gunung Kidul lacks the necessary infrastructure to disseminate information about the availability of blood bags efficiently. In the current era of digital advancement, the slow pace of information distribution is notably ineffective, thus integrating the system with Android technology is a strategic solution. sThis blood donation application is designed for donors who lack information about blood donation activities and for organizations wishing to conduct such events. The development of this Android application system involves experimental data collection methods, including observation, interviews, literature study, and documentation. The unit testing employs the Waterfall methodology. The application is developed using the Kotlin programming language, with the aid of Android Studio software
Digital Library Development Strategy at Universitas Muhammadiyah Tapanuli Selatan

The advent of Information and Communication Technology (ICT) has significantly transformed library paradigms, shifting from traditional manual systems to digital platforms, a change particularly evident in academic libraries. This study focuses on the University of Muhammadiyah Tapanuli Selatan, aiming to develop a strategic framework for its digital library to enhance services in alignment with the tridharma of higher education. Employing a qualitative, descriptive methodology, the research incorporates both primary and secondary data sources. The analysis involves data reduction, presentation, and conclusion drawing. Results show that the University's library, accessible through Windows and Android applications, has experienced a marked increase in user engagement from 2020 to 2023. However, despite this growth, the development of the digital library requires further enhancement to fully realize its potential and meet user expectations. This study underlines the need for ongoing development strategies in digital libraries to keep pace with technological advancements and evolving user needs.
Development of Android-Based 3D Building Augmented Reality Application at Jogja Student Islamic Boarding School 2

Islamic boarding schools are pivotal in providing religious education for Muslims in Indonesia. Despite their widespread presence, detailed knowledge about these institutions, particularly their architectural design, remains limited. Prospective students and the public often rely on internet images for information, leading to a partial understanding of the physical structure of these schools. This study introduces an innovative solution through the development of an Augmented Reality (AR) mobile application specifically designed for the Jogja 2 Islamic Boarding School. Augmented Reality technology effectively integrates 2D and 3D virtual objects into a real-world environment, offering an immersive, real-time experience. By utilizing the waterfall methodology in its development, this application aims to provide an in-depth, three-dimensional exploration of the Jogja 2 boarding school's infrastructure. This tool is intended to assist potential students and interested individuals in gaining a comprehensive understanding of the school's architectural layout and design dynamically and interactively.
The Shopee Application User Reviews Sentiment Analysis Employing Naïve Bayes Algorithm

With the significant growth of internet use in Indonesia, there has been a surge in online business activity. The convenience offered by online platforms is increasingly in demand because it allows consumers to shop without being bound by a certain time or location. Before making a purchase, consumers tend to look for information first through various sources such as reviews on blogs, Instagram, TikTok, or reviews on the YouTube platform which is integrated in the application. This research adopted a method that included planning, literature study, data collection, and data processing using a dataset from the Play Store application which was taken using the Python library with an initial amount of 5000 data. After a manual filtering process which involved removing slang words, eliminating duplications, and normalizing punctuation marks, the remaining data was 3946. The application of the Naïve Bayes algorithm in this research uses probability methods to classify and predict 3141 training data and 805 test data, with Python library help. The accuracy calculation results show satisfactory performance, with an accuracy of 86.00%, precision of 80.74%, recall of 78.13%, and f1-score of 79.00% on a dataset of 3946. Analysis from this research shows the dominance of positive sentiment in 2050 data, while sentiment negative amounted to 1199 data. The amount and quality of training data plays an important role in system predictions, where high data quality provides better accuracy in predicting sentiment classes
Multiscale feature fusion network for monocular complex hand pose estimation

Abstract Hand pose estimation based on a single RGB image has low accuracy due to the complexity of the pose, local self‐similarity of finger features, and occlusion. A multiscale feature fusion network (MS‐FF) for monocular vision gesture pose estimation is proposed to address this problem. The network can take full advantage of different channel information to enhance important gesture information, and it can simultaneously extract features from feature maps of different resolutions to obtain as much detailed feature information and deep semantic information as possible. The feature maps are merged to obtain the hand pose results. The InterHand2.6M dataset and Rendered Handpose Dataset (RHD) are used to train the MS‐FF. Compared with the other methods, the MS‐FF obtains the smallest average error of hand joints, verifying its effectiveness.
The Moderated Mediating Effect of Career Aspiration in the Effects of Family Support and Career Adaptability on Career Preparation Behavior of Vocational High School Students

This paper aims to analyze the moderated mediating effect of career aspirations in the effects of family support and career adaptability on career preparation behavior in vocational high school adolescents. The subjects of this study were 535 students attending vocational high schools located in Daegu. The period of investigation is from January to March 2023. The analysis results derived from this study are as follows. First, it was found that the higher the family support perceived by the adolescents in the vocational high school, the higher the career preparation behavior. Second, the higher the family support of the vocational high school students, the higher the career adaptability. Third, it was found that career adaptability plays a mediating role in the effect of family support in vocational high schools on career preparation behavior. Fourth, it was found that career aspiration played a moderating role in the effect of career adaptability perception on career preparation behavior of vocational high school students.
Interaction between National Youth Policy and National Youth Center - Focusing on the Pyeongchang National Youth Center -

This study examines the implementation of youth policy in the field, focusing on the National Pyeongchang Youth Center(PNYC), Korea's first national youth center with a 25-year history. It explores how the center executes youth policy and the resulting impact on youth. The findings reveal that the PNYC plays a pivotal role as a key disseminator of youth policy, supporting youth development and empowerment through diverse programs and activities. This research underscores the significance of the National Pyeongchang Youth Center and provides insights into the practical implementation of youth policy and the implications for youth activities. It also suggests future research directions, including comparative studies across different institutions, exploration of youth participation and experience, and analysis of the policy decision-making process.
Learning to Teach Online during the Pandemic: Chilean EFL Pre-service Teachers’ Experiences during their First Online Practicum

Resumen In order to continue delivering lessons to prevent students’ learning from being affected as a result of the pandemic, education systems around the world transitioned to distance learning. However, the transition process was far from being untroubled. Likewise, primary, secondary, and higher education in Chile experienced major disruptions. In 2020, schools around the country closed as a result of the pandemic, leading most institutions to migrate to online teaching. This change also seriously affected teacher education programs in Chile; carrying out a face-to-face practicum in a pandemic context resulted non-viable, forcing teacher educators and institutions to abruptly implement the online mode of delivery. The main aim of the present article is to explore a group of Chilean EFL pre-service teachers’ perceptions with regards to their online practicum carried out under circumstances characterized by high levels of uncertainty and the need to rapidly adjust to new conditions. More specifically, the article focuses on two key aspects. On the one hand, it outlines the pre-service teachers’ perceptions with regards to the main challenges and opportunities encountered in this experience. On the other hand, the article explores pre-service teachers’ beliefs with regards to the impact that this experience might have on their teaching practice in the short and long term. The present study employed a qualitative design with an exploratory and descriptive approach. In order to take into account the voices of the participants, eight individual semi-structured interviews with pre-service teachers were carried out. The main findings refer to three sets of challenges and opportunities: the focus on technological and pedagogical skills as opposed to content; autonomy in the classroom paired with neglect on the side of the mentor teacher; and the ability to build bonds as opposed to being affected by the pupils’ lack of motivation. Furthermore, the study also showcases that the pre-service teachers believe that their first online practicum equipped them with useful ICTs skills that will have a positive impact both on their teaching practice in the short and long term and in their employability. Nevertheless, doubts were also raised regarding how the new skills would actually contribute to their development as teachers in regular, face-to-face contexts. The study helps understanding the effects of the pandemic on initial teacher training, which is a necessary step towards reshaping this process for future generations. Keywords practicum EFL teacher training Covid-19 English