Reviewerly/exHarmony huggingface dataset:
PPChain: A Blockchain for Pandemic Prevention and Control Assisted by Federated Learning

Taking COVID-19 as an example, we know that a pandemic can have a huge impact on normal human life and the economy. Meanwhile, the population flow between countries and regions is the main factor affecting the changes in a pandemic, which is determined by the airline network. Therefore, realizing the overall control of airports is an effective way to control a pandemic. However, this is restricted by the differences in prevention and control policies in different areas and privacy issues, such as how a patient’s personal data from a medical center cannot be effectively combined with their passenger personal data. This prevents more precise airport control decisions from being made. To address this, this paper designed a novel data-sharing framework (i.e., PPChain) based on blockchain and federated learning. The experiment uses a CPU i7-12800HX and uses Docker to simulate multiple virtual nodes. The model is deployed to run on an NVIDIA GeForce GTX 3090Ti GPU. The experiment shows that the relationship between a pandemic and aircraft transport can be effectively explored by PPChain without sharing raw data. This approach does not require centralized trust and improves the security of the sharing process. The scheme can help formulate more scientific and rational prevention and control policies for the control of airports. Additionally, it can use aerial data to predict pandemics more accurately.
Precision form measurement of biconic surfaces using scanning Fizeau interferometry

Biconic surfaces are among the most fundamental freeform surfaces and have important applications in the ophthalmic industry. They are characterized by just four parameters, namely the two radii and two conical constants in the x- and y-direction, and they have even symmetry along x and y. As for many other optical surface types, the manufacturing of these surfaces requires form measurements with a precision of a tenth of a wave. We introduce an approach to measure the form of biconic surfaces using Fizeau interferometry. The approach builds on concepts we have used in the past for the measurement of aspheres and toric surfaces. A combination of sub-aperture data acquisition, fringe order tracking and distance function removal produces a series of sub-aperture deviation maps which can then be combined into a full field deviation map of the entire surface. This final map can be further analyzed for errors in the four design parameters as well as higher-order form errors. In addition, it is possible to determine the orientation of the principal curvatures of the test part with respect to its mount in the instrument. We discuss the details of the measurement procedure, show first measurement examples, and discuss how the method can be validated using toric and aspheric surfaces which can be measured as such but can also be measured as biconics allowing for comparisons.
Multi-Plane Neural Radiance Fields for Novel View Synthesis

Novel view synthesis is a long-standing problem that revolves around rendering frames of scenes from novel camera viewpoints. Volumetric approaches provide a solution for modeling occlusions through the explicit 3D representation of the camera frustum. Multi-plane Images (MPI) are volumetric methods that represent the scene using front-parallel planes at distinct depths but suffer from depth discretization leading to a 2.D scene representation. Another line of approach relies on implicit 3D scene representations. Neural Radiance Fields (NeRF) utilize neural networks for encapsulating the continuous 3D scene structure within the network weights achieving photorealistic synthesis results, however, methods are constrained to per-scene optimization settings which are inefficient in practice. Multi-plane Neural Radiance Fields (MINE) open the door for combining implicit and explicit scene representations. It enables continuous 3D scene representations, especially in the depth dimension, while utilizing the input image features to avoid per-scene optimization. The main drawback of the current literature work in this domain is being constrained to single-view input, limiting the synthesis ability to narrow viewpoint ranges. In this work, we thoroughly examine the performance, generalization, and efficiency of single-view multi-plane neural radiance fields. In addition, we propose a new multiplane NeRF architecture that accepts multiple views to improve the synthesis results and expand the viewing range. Features from the input source frames are effectively fused through a proposed attention-aware fusion module to highlight important information from different viewpoints. Experiments show the effectiveness of attention-based fusion and the promising outcomes of our proposed method when compared to multi-view NeRF and MPI techniques.
Library and Information Services in the Library User’s Personal Account

A priority for modern libraries is the comprehensive transformation of the library and information service model in the context of universal digitalization. Digitalization of the library and information sphere is expressed in the emergence of new methods involving the use of innovative software tools as an alternative to the traditional approach. Through the implementation of digitalization initiatives, libraries are creating managed electronic environments with a wide range of digital library and information services. Software tools oriented towards the provision of these kinds of services include the creation of a user’s personal account on the library website. Today a personal account is an essential attribute of the websites of many national and university libraries, both local and foreign. The aim of the article is to analyze the possibilities of a personal account in terms of providing library and information services, including bibliographic ones, to remote library users. The article discusses ways of online registration and authorization in a personal account, its services available to users, as well as software tools to make the user’s work comfortable. Personal account is a tool for managing a set of connected services, which is constantly being improved and supplemented with new services. The range of services available to the user can vary, reflecting the specifics and size of the library. The features of the personal account are illustrated by examples from Russian and foreign libraries. The personal account has been successfully used to provide bibliographic services to support research and teaching activities. Based on the results of the analysis of the information in the personal account, libraries make decisions aimed at increasing loyalty, formation of individual offers to improve the comfort of service for users. The personal account is predominantly used in university libraries, where it is a part of the integrated information and educational environment. Using the potential of the virtual working environment is an opportunity for libraries to find their place in the digital world.
Aspect-Based Sentimental Analysis for Travellers’ Reviews

Airport service quality evaluation is commonly found on social media, including Google Maps. This valuable for airport management in order to enhance the quality of services provided. However; prior studies either provide general review for topics discussed by travellers or provide sentimental value to tag the entire review without specifically mentioning the airport service that is behind such value. Accordingly; this work proposes using aspect based sentimental analysis in order to provide more detailed analysis for travellers’ reviews. This works applied aspect based sentimental analysis on data collected from Google Map about Dubai and Doha airports. The results provide tangible reasons to use aspect based sentimental analysis in order to understand more the travellers and spot airport services that are in need for improvement.
The Number Systems Tower

For high school and college instructors and students, this paper connects number systems, field axioms, and polynomials.It also considers other properties such as cardinality, density, subset, and superset relationships.Additional aspects of this paper include gains and losses through sequences of number systems.The paper ends with a great number of activities for classroom use.
Improving the Performance of Searchable Symmetric Encryption by Optimizing Locality

Both individuals and organizations prioritize data security and privacy, leading to an increasing focus on technological solutions that emphasize these aspects. Searchable symmetric encryption stands out as a prominent choice for secure storage and search of encrypted data on cloud servers, contributing to this objective. While searchable symmetric encryption offers numerous benefits, it also faces certain challenges, particularly when dealing with large databases. One significant challenge is poor performance, often attributed to poor locality. Visiting multiple locations can significantly increase the time required for data retrieval. Additionally, optimization methods aimed at improving locality can sometimes impact read efficiency or result in excessive storage of the encrypted index on the cloud server. In this paper, we present a scheme that effectively addresses these issues. We have enhanced the encrypted inverted index storage mechanism to improve information retrieval performance. Our scheme achieves optimal locality O(1) and optimal read efficiency in O(1), resulting in a significant increase in retrieval speed. Through experimentation with real-world data, we have demonstrated the practicality, accuracy, and security of our scheme.
Role Based Access Control Using Biometric the in Educational System

The purpose of a secure e-learning system based on cloud computing is to allow instructors and students to access their accounts at any time and from anywhere. These types of systems work to ensure that their users (instructors and students) are truly enrolled in the school or institute to prevent unauthorized users from accessing the resources and components of the system. Furthermore, the traditional authentication techniques used in the majority of educational systems suffer from several issues, such as cyber security attacks and weak management of resources. So, some students could be eager to take advantage of such a system's flaw in an effort to cheat. User authentication and end-user monitoring are more difficult in this situation. Multifactor adaptive authentication techniques are used to implement a system with simultaneous authentication. The proposed scheme system offers an effective, affordable, and human intervention-adaptive authentication and monitoring solution for e-learning environments. Additionally, our work can resist cyber security and contains some good metrics like mutual authentication, user anomalies, and others. In this paper, the proposed scheme system uses a two-factor authentication system based on Asymmetric Scalar Product Preserving Encryption (APSE) and fingerprint biometrics for managing and generating a user's account in a secure way. Our work also achieves a good balance between performance and security complexity compared to the state-of-the-art. So, we achieve good results for 1.69 ms for computation and 1280 bits for communication.
IMPROVING BEGINNING CALCULATING ABILITY THROUGH MODIFIED COGGLAK MEDIA IN CHILDREN AGED 4-5 YEARS

Researchers will conduct this research aiming to improve the numeracy skills of children aged 4-5 years through the media of saving corn at Pembina II Sooko Public Kindergarten, Mojokerto. This study used the Classroom Action Research (CAR) method which was carried out using two cycles of action. The subjects of this study were 26 children from Group A1 of TK Negeri Pembina II Sooko. Data collection techniques through observation, interviews, and documentation. The results showed that there was an increase in the numeracy skills of children aged 4-5 years through the "Modified Congklak" media. The results obtained in Cycle I were 30.8% due to several causal factors, namely the child was still confused if the number taken was 5 but the corn that was put into the glass cup was less than 5. So in Cycle II it is hoped that it can be followed up by motivating children through stories and giving rewards, training children repeatedly, and doing more interesting counting activities. In Cycle II, obtaining 76.9% stated that it had reached an indicator of success. The learning process using Modified Congklak media can improve the numeracy skills of children aged 4-5 years. Thus it can be concluded that through Modified Congklak media it can improve numeracy skills in group A1 children at Pembina II Sooko Public Kindergarten.
Application of artificial intelligence video feedback system in College Teaching

This paper introduces the application of artificial intelligence video feedback system in college teaching. With the rise of online education and distance education, artificial intelligence technology is becoming an important way of university education, and also an effective means to improve the teaching effect and quality. This video feedback system provides personalized feedback by analyzing students' performance, and helps teachers better guide students' learning. In practice, AI video feedback system can be combined with existing online education resources such as online education platform to further deepen online education mode and innovate teaching methods. Students can learn in free time, and teachers can also use the online education platform to interact with students, and constantly improve and adjust teaching strategies in the teaching process.
BOWLING MATHEMATIC GAME TO IMPROVE BEGINNING CALCULATING ABILITY OF CHILDREN 5-6 YEARS OLD

The purpose of this research is to improve the initial numeracy skills for children aged 5 to 6 years through bowling mathematics games through class action methods with the Kemmis and MC Taggart models. Data was collected through observation sheets and analyzed through simple descriptive statistics. The subjects of this study were 25 children aged 5 to 6 years and the results concluded that the percentage of completeness on the indicator mentioned the pre-action number symbol was 48%, cycle 1 was 60% and cycle 2 was 87%, counting pre-action objects was 40%, 55% in cycle 1 and 84% in cycle 2, then using numbers to calculate pre-action by 28%, cycle 1 by 43% and cycle 2 by 81%. These results can be concluded that the bowling mathematics game can improve the ability of children aged 5 to 6 years in starting arithmetic.
Evaluating the Effectiveness of Different Machine Learning Approaches for Sentiment Classification

This study presents a comparison of four different machine learning algorithms for sentiment analysis on a small subset of the AR-P (Amazon Reviews - Polarity) dataset. The algorithms evaluated are multilayer perceptron (MLP), Naive Bayes, Decision Tree, and Transformer architectures. The results show that the Transformer-based DistilBERT model performed the best with an accuracy rate of 96.10%, while MLP had a better performance than the other remaining methods. Confusion matrices and ROC curves are provided to illustrate the results, and a comparison with previous studies is presented. The study concludes that the results can serve as a basis for future work, such as using larger datasets or comparing the performance of algorithms on different tasks. Overall, this study provides insights into the use of traditional machine learning and modern deep learning methods for sentiment analysis and their potential applications in real-world scenarios.
DEVELOPMENT OF CANVA-BASED EDUCATIONAL GAMES ON INTRODUCTION TO FRUIT TYPES

Education provides the brightness of human life to be more directed according to the development of science and technology. At present technology is the main thing used in the field of education, for example it is used in learning media in schools. The purpose of this development research is to develop an educational game about fruit types with the Canva application for early childhood. The method used is research and development (R&amp;D) with a qualitative descriptive approach, namely explaining the steps for making learning media material for identifying fruit types with the Canva application in early childhood and using the ADDIE model (analysis, design, development, implementation, evaluation) there are 5 stages and research focus using 3 stages, namely analysis, design, and development. Learning media with the Canva application produce educational games that are interesting and provide a variety of colors in learning that have the potential to be good learning media used during face-to-face and virtual face-to-face learning with educational game learning content material for identifying fruit types with games which are divided into three categories, namely guess the type fruit according to the characteristics of the fruit listed, guess the type of fruit by choice, and complete the word name of the fruit.
IMPROVING STUDENT'S READING INTEREST THROUGH THE JIGSAW COOPERATIVE LEARNING MODEL IN ELEMENTARY SCHOOL

The habit of writing and reading in Indonesian society is still very low or not fully developed. In the interest of realizing a generation who likes to read, surely what must be grown first is the interest in reading in each individual. This problem encourages teachers to be able to provide optimal stimulus in fostering interest in reading in student from an early age while still prioritizing child-centered learning. This research implemented a jigsaw cooperative learning model. The research design used is Classroom Action Research (CAR) which includes two research cycles. The results second cycle show that 87% of student managed to reach the good category. Research using the Jigsaw Cooperative learning model on student's reading interest showed a significant increase. Based on the results of the research above, it can be concluded that the application of the Jigsaw cooperative learning model can increase student's reading interest.
IMPROVING CHILDREN'S COGNITIVE ABILITY THROUGH BLOCK EDUCATIONAL GAMES

This research was carried out with the aim of providing knowledge or choices to parents and teachers or educators that cognitive development can be enhanced through playing educational games with blocks. This research is a qualitative descriptive research. With data collection techniques observation, interviews, and documentation. The research subjects were 20 students of class B TK Darussalam Plus Yogyakarta. The results showed that there was an increase in children's cognitive abilities through educational games in the form of blocks. This is evidenced by the increase in children's cognitive abilities with the application of educational games, such as being able to classify different according to type and color, compare shapes around them, understand various number concepts, distinguish between large and small, long and short, time, space, and able to make a good picture or design.
KNOWING OBJECT LITERACY IN DEVELOPING CHILD LITERACY

This study aims to collaborate theory with practice in the form of real events in the field. This study also describes the importance of literacy which is developed through the method of playing object literacy. This research can develop children's language patterns, especially those related to language skills and language skills that are applied in everyday life. The research method used is descriptive qualitative with literature in the form of photos, notes, and books. The result of this research is the lack of intensive communication and interaction with children. Although more than one child is not an obstacle to forming and developing language patterns, especially suitability and coherence with the object being observed. The researcher tries to provide a way of stimulating education with the object literacy method and the researcher starts with fairy tales using hand puppet media. This is what the researcher does with the auditory stage and in that way the child will try to record; starting from vocabulary, intonation, and structure. It is hoped that there will be changes in language skills, so that in the future children will be confident to develop more regular and complex language patterns.
An Empirical Study of the Effect of Emotional Intelligence on Job Performance the Case Study of Educational Non-Governmental Organizations During the Covid-19 Outbreak

The Third-sector organizations, known as Non-Governmental Organizations (NGOs) working on had an essential role in improving education, building human capital, sustainable development, humanitarian aid, and raising entrepreneurs, especially in the areas of political conflict and increased poverty.This research aims to analyze the effect of Emotional Intelligence on Job Performance in three selected Educational and human aid NGOs in the Kurdistan Region/Iraq during the Covid-19 pandemic.This research is claimed to be novel to study the concepts in businesses on NGOs.The author used a self-administered questionnaire with included two validated measures and demographic items.The data has been collected from 83 respondents working as employees in the NGOs selected.The author used Pearson correlation, ANOVA, and linear regression to justify the hypothesis developed.The results show a strong positive relationship between EI and job performance.The EI positively and significantly affects Job Performance and there is no difference between the genders of the study in terms of Emotional Intelligence and Job performance.The study recommends educational and human aid NGOs consider EI as an important factor in increasing the performance of their employees, and this research is to be a foundation for further research to understand the application of management concepts of Businesses in the context of NGOs.
Teachers’ Perceptions, Preparations, And Challenges in the Implementation of Limited Face-To-Face Classroom Interaction in the New Normal

Teachers have varied perceptions in the implementation of the limited face-to-face classroom interaction.Being the implementers, teachers go through series of preparations in ensuring its success while adhering to the guidelines imposed by the authorities to safeguard the health of both teachers and students.Varied teaching strategies and coping mechanisms were utilized to cater learners' needs and confront challenges.Challenges will always be part of the teaching-learning process, though teachers went on rigorous preparations in the implementation of the limited face-to-face classroom interaction.However, it does not obstruct teachers' focus to cope with these challenges and to innovate strategies to help students achieve their academic success.It is revealed that teachers' flexibility, optimism, and their commitment to their profession, paired with support from the administration were of great help during the implementation of the limited faceto-face classroom interaction in the new normal.