Reviewerly/exHarmony huggingface dataset:
BOOK RECOMMENDATION SYSTEM USING PYTHON

An innovative book recommendation tool called BookWise was created to help readers get individualized book suggestions based on their unique preferences. Effective recommendation systems are now more necessary than ever to guide readers through the overwhelming amount of options given the exponential expansion of the digital book market. Advanced machine learning algorithms and methodsfor natural language processing are used by BookWise to analyze a variety of features of books, including genre, author, narrative, and style, as well as user information like reading habits, ratings, and history. These elements are combined by BookWise to produce precise recommendationsthat are pertinent to the preferences of each user. BookWise's ability to learn from and adjust to the evolving preferences of its users over time is at the heart of the program. The system uses collaborative filtering and content-based filtering approaches to continuously gather user feedback on suggested books and take user interactions into account. By doing this, it is able to make increasingly accurate and interesting recommendations to users. By implementing a user review and rating system, BookWise also encourages social involvement and a sense of community among its members. Users can communicate with people who share their interests in literature, discussreviews, and offertheirthoughts. This community-driven strategy improves the quality of suggestions while also enhancing the reading experience by encouraging interactions and relationships amongst book lovers. Furthermore, BookWise is created to be very user- friendly, giving cross-platform compatibility, including online and mobile applications, to make sure users can get their tailored recommendations wherever they are and wheneverthey want. The system also offers a simple and user-friendly design that makes it simple to navigate and explore books of all genres, new releases, and popular works. Through thorough user testing and review, BookWise's efficacy has been confirmed, proving its capacity to provide precise and pleasing recommendations that are in line with consssumers' interests. BookWise represents a significant advancement in the field of book recommendation systems by providing a potent tool to improve reader experiences, promote literary research in the digital age, and ease discovery. Keywords—Personalize book recommendation; recommendation system; clustering; machine learning
OPTIMIZATION OF PLANTING PATTERNS ON PADDY PLOTS IN PURI VILLAGE, PURI DISTRICT, MOJOKERTO REGENCY, EAST JAVA USING A LINEAR PROGRAM

The research site is located in one of the hamlets in Puri village, which has an agricultural land area of approximately 25 hectares. Because of its fertile soil conditions, the land is very suitable for agriculture. However, the agricultural productivity in Puri village has decreased due to changing weather conditions. Puri village, Puri district, Mojokerto regency, has a flat landscape. The duration of the dry season is slightly longer, affecting the availability of water and causing a change in the initial cropping period. As a result, the cropping pattern in the village is not appropriate, leading to a decrease in agricultural productivity. To solve these problems, an optimal cropping pattern needs to be planned to increase agricultural productivity in the village. In order to plan the optimal cropping pattern, the first thing that needs to be done is to calculate the availability of existing water. Then, the need for irrigation water should be calculated. Using the two sets of calculation data, the optimal cropping pattern can be planned with linear program. The analysis is revealed that Puri village has an optimal cropping pattern with a Paddy-Corn-Corn cropping model and an initial planting period in December period 2.
Bibliographic Transition in France: work in progress

This article presents the current state of bibliographic transition in France, the approach and the organization that were applied to make library catalogues compatible with semantic web technologies and bibliographic data on the web.In order to achieve this goal, it is necessary to move to entity-based cataloguing built on the IFLA LRM model.After a thorough study of the RDA standard, which was the first step to take, France has chosen to keep some autonomy and create a national cataloguing standard, RDA-FR, which is an Anglo-American standard adapted to the French context.In order to implement this change, the Bibliographic Transition programme has been assigned to two national bibliographic agencies with three operational pillars representing the three facets of the program: standardisation, training and support for the evolution of systems and data.The choices and the issues are given in details, as well as the missions and achievements of the groups.This organisation has been established to ensure a regular flow of information between the operational and strategic levels on one side and between different groups on the other side.Overall consistency is one of the key features of the programme whose role is to bring together and represent all French libraries and French cultural institutions while taking into account their needs and the needs of their users.
Comparison of machine learning training sampling schemes for induction machine modeling

The aim of the paper is to demonstrate the modeling of an induction machine using a chosen machine learning technique, followed by a comparison of the training sampling schemes for this technique.A simple 3-phase induction machine with an axially slitted solid rotor has been selected for the case study, where FEM-based program Ansys Electronics Desktop has been used for its calculation.A total of 3 training schemes were considered and compared with each other for the machine learning technique.Some of the comparison results are given and discussed at the end of this paper.The described methodology can be used to accelerate the design and optimization of any type of electrical machine.
Supplement to Volume 38: Proceedings of the ISHE Summerschool in Brazil, Czech Republic and the United States of America, 2023

Few studies have examined friendships among twins.This is the first study in Brazil and is part of the Painel USP de Gêmeos.A previous study conducted with British twins in childhood has shown that the number of friends did not vary, but MZ shared more friends than DZ (MZ>DZss>DZos).Our aim was to compare the number of friends and the proportion of friends in common among monozygotic (MZ), same-sex (DZss) and opposite-sex (DZos) dizygotic twins, and to investigate the association with their well-being.Eighteen pairs of Brazilian twins aged 8-14 (MZ=8; DZss=6; DZos=4) represented their friendship network on the Pictorial Representation of Friends and answered a 5-item Well-Being Scale validated in Brazil.Non-parametric Kruskal Wallis tests were used.Additional pairwise comparisons were conducted using the Mann-Whitney test with Bonferroni correction and showed that common friends (χ(2)²=9.078;p=0.011) and proportion of friends (χ(2)²=9.143;p=0.010) was lower in the DZso group relative to both the MZ and DZss.The comparison of number of friends and wellbeing showed no significant effects.Our research is in line with previous studies suggesting that similar individuals are likely to have a considerable overlap of friends, whereas opposite-sex twin pairs have separate social groups.The results may contribute in the fields of psychology and education to deepen the understanding of the specificities of the twin relationship and the practical implications on its insertion in the school context.
Deployment of Threshold Signatures for Securing Bitcoin Transactions

Blockchain technology, especially Bitcoin, has revolutionized how we think about and manage financial transactions.However, with the increasing demand and usage of blockchain technology, the security of cryptocurrency wallets has become a critical concern.Threshold signatures offer a promising solution to this problem, allowing multiple parties to sign a transaction without revealing their private keys.This article presents an Android mobile Bitcoin wallet application that uses Schnorr-based threshold signatures.The application also deploys smartwatch integration for enhanced security and usability.This integration provides an additional layer of security by requiring physical confirmation from the user before approving any transaction.Our implementation provides a secure and efficient platform for managing Bitcoin assets using threshold signatures while also providing an intuitive and easy-to-use interface for interacting with the application.
Tool Assisted Empirical Approach to Reusability Models Assessment

In software development, reuse became an important aspect in increasing productivity and performance and in reducing costs. The extend to which software can be reused have been captured by several reusability assessment models proposed in literature. In this chapter we propose an empirical analysis of three reusability models with the scope of long term evaluation of reusability in open source software. We successfully reproduced the models and applied them to several versions of large Java open source projects. We investigate the long term evolution of reusability, its relation to metrics and other quality factors. Results show a significant difference in the reusability models, but reflect a clear influence of complexity, cohesion, coupling, size and documentation.
The Development of Flipbook Based on the Addie Model in Science Learning for Elementary School Students

This study is motivated by the lack of use of technology-based media in elementary schools. With the aim of knowing student learning outcomes after using the flipbook the characteristics of living things and user responses. The research was conducted to describe flipbook analysis, design, development, implementation, user response, student learning outcomes and evaluation of flipbook characteristics of living things. Flipbook is a form of presentation of book learning media in virtual form. The method used in this research is D&amp;D (design and development) and used the ADDIE model (analyze, design, development, implementation, and evaluation)). The findings when research students have never learned to use design technology are made in Canva for development into an android application, tested for feasibility by media, language, material, learning experts with very decent category results with an average score of 82.6%. The implementation was carried out achieved a very good response from users with an average of 88.9% and the average student learning outcomes increased as seen from an average of 32.6 to 73.8. After the flipbook was tested, many evaluations had to be done, such as suggestions from students, namely the volume of the audio sound was still small and relatively inaudible when used if there were other students speaking so that their voices clashed. In general, this flipbook of the characteristics of living things is appropriate for third grade students in elementary school. Keywords: Flipbook, Characteristics of Living Things, Elementary School
Retracted: Detection of Diseases Using Machine Learning Image Recognition Technology in Artificial Intelligence

[This retracts the article DOI: 10.1155/2022/5658641.].
Activation of nonlocality for Bell local states

Bell’s nonlocality—correlations between two distant, entangled particles that cannot be explained by physical theories based on local causality—remains one of the most celebrated results of quantum foundations. However, these nonlocal correlations eventually disappear under the presence of noise. In this experimental work, we show that nonlocality, inaccessible for noisy states in the two-party scenario, can be activated in a three-node photonic network structure with a single copy of the state. Our results open up new possibilities for network-based quantum information processing applications, central for the development of a future quantum internet.
Quantum photonic neural networks with imperfect components

Reconfigurable photonic integrated circuits (PICs) for quantum optical information processing are now routinely made in foundries with hundreds or thousands of components. Such PICs rely on linear optics, meaning that all photon-photon interactions are probabilistic, and hence that complex protocols that, for example, produce entanglement or graph states do so at low rates. Adding optical nonlinearities to the circuits provides an activation function analogous to that of classical neural networks, enabling deterministic photon-photon protocols in ideal circuits. Here, we discuss the next step: quantum photonic neural networks made from more realistic – i.e. imperfect – components. We show that these are capable of near-deterministic entanglement generation, when imperfections such as losses, imperfect routing and sub-optimal nonlinearities are balanced against network size. These results provide a design for real quantum photonic neural networks and demonstrate that they may play important roles in emerging quantum technologies.
The INOVMineral Project’s Contribution to Mineral Exploration—A WebGIS Integration and Visualization of Spectral and Geophysical Properties of the Aldeia LCT Pegmatite Spodumene Deposit

Due to the current energetic transition, new geological exploration technologies are needed to discover mineral deposits containing critical materials such as lithium (Li). The vast majority of European Li deposits are related to Li–Cs–Ta (LCT) pegmatites. A review of the literature indicates that conventional exploration campaigns are dominated by geochemical surveys and related exploration tools. However, other exploration techniques must be evaluated, namely, remote sensing (RS) and geophysics. This work presents the results of the INOVMINERAL4.0 project obtained through alternative approaches to traditional geochemistry that were gathered and integrated into a webGIS application. The specific objectives were to: (i) assess the potential of high-resolution elevation data; (ii) evaluate geophysical methods, particularly radiometry; (iii) establish a methodology for spectral data acquisition and build a spectral library; (iv) compare obtained spectra with Landsat 9 data for pegmatite identification; and (v) implement a user-friendly webGIS platform for data integration and visualization. Radiometric data acquisition using geophysical techniques effectively discriminated pegmatites from host rocks. The developed spectral library provides valuable insights for space-based exploration. Landsat 9 data accurately identified known LCT pegmatite targets compared with Landsat 8. The user-friendly webGIS platform facilitates data integration, visualization, and sharing, supporting potential users in similar exploration approaches.
Anomaly Detection in Time Series: Current Focus and Future Challenges

Anomaly detection in time series has become an increasingly vital task, with applications such as fraud detection and intrusion monitoring. Tackling this problem requires an array of approaches, including statistical analysis, machine learning, and deep learning. Various techniques have been proposed to cater to the complexity of this problem. However, there are still numerous challenges in the field concerning how best to process high-dimensional and complex data streams in real time. This chapter offers insight into the cutting-edge models for anomaly detection in time series. Several of the models are discussed and their advantages and disadvantages are explored. We also look at new areas of research that are being explored by researchers today as their current focuses and how those new models or techniques are being implemented in them as they try to solve unique problems posed by complex data, high-volume data streams, and a need for real-time processing. These research areas will provide concrete examples of the applications of discussed models. Lastly, we identify some of the current issues and suggest future directions for research concerning anomaly detection systems. We aim to provide readers with a comprehensive picture of what is already out there so they can better understand the space – preparing them for further development within this growing field.
Social Media Addiction and Academic Performance of Social Studies Students in Upper Basic Schools in Delta State

This study examined social media addiction on the academic performance of Social Studies students in upper basic education in Delta State. The study adopted a correlational research design. The sample size comprised 381 Basic 9 students in Delta State, selected through a multistage sampling method. The instruments used to generate data for the study were questionnaire and student’s past results. The research questions were analysed using Pearson’s product moment correlation coefficient, while the hypotheses were tested using regression and Fisher-Z statistics at 0.05 level of significance. The findings of the study revealed that there is a significant relationship between social media addiction and academic performance; there is no significant influence of gender on the relationship between social media addiction and academic performance of Social Studies students; and that there is no significant influence of location on the relationship between social media addiction and academic performance of Social Studies students. The study recommended amongst many others, that the students should be advised to always use social media platforms to support their studies and for academic discussions.
TECHNOLOGY IN EDUCATION

With the advent of innovative technology, many traditional schools have resorted to modern techniques to facilitate student learning. Early steps recognize the role of technology in education. Which indicates the importance of audio-visual equipment like tele media, recording media, computer etc. Thus, educational technology emphasizes the art of employing so-called hardware, innovative media, and machine industry methods for educational purposes. It has now become clear that the systematic way in which technology is used to achieve a purpose is as important as the use of technology. Today the software aspect of educational technology has reached an important point i.e. it is useful in molding behavioural practices or in other words useful for solving problems of promoting learning and motivation. The most widely known meaning of educational technology today is more special than the acquisition of its hardware or software.
Analisis Sentimen Tanggapan Masyarakat Terhadap Calon Presiden 2024 Ridwan Kamil Menggunakan Metode Naive Bayes Classifier

Reaction to public facts about the election of the presidential candidate Ridwan Kamil, which will later be obtained, the data is taken from Twitter based on these problems, it is necessary to do sentiment analysis research. Based on the results of this study, the classification process for the Naïve Bayes Classifier has 3 scenarios for dividing training data and test data, namely with 90%:10% training data, the test data produces an accuary value of 85.43%, a recall value of 100.00%, and a precision of 85.33%. For training data 80%: 20% of the test data produces an accuracy value of 86.38%, a recall of 100.00% and a precision value of 86.38% and for data on the distribution of training data 70%: 30% of the test data produces an accuary value of 84.29 %, 100.00% recall and 84.29% precision. From the tweet data that has been used, there are 1262 positive comments and 242 negative comments. These results prove that the Naïve Bayes classifier is very good for conducting sentiment analysis on Twitter comments about the 2024 presidential candidate Ridwan Kamil. The naïve Bayes classifier process gets the highest accuracy value of 86.38% by dividing the training data 80%:20% test data.
Trial Vending Machine Providing Medicine to the Elderly Case Study of Bhakti Luhur Nursing Home

Vending machine is a machine made to provide various needs of the community. This tool is intended to reduce physical contact in the Covid-19 era and provide Indonesian people experience shopping in the modern era. In this study, a vending machine was made to provide medicines in nursing homes to make it easier for nurses in nursing homes to prepare for the needs of medicines for the elderly who have comorbid diseases such as heart, diabetes, hypertension and shorten time and physical contact in the Covid-19 era. In this research using the ESP8266 microcontroller as a microcontroller and Telegram's IoT (Internet Of Things) for media data base notifications when drugs have been taken. RFID (Radio Frequency Identification) as a card-shaped data identification tool for each elderly person has been programmed according to the diseases suffered by seniors. For the drug dispensing drive system, it uses a servo motor. For information on whether the drugs issued are appropriate, an LCD (Liquid Crystal Display) is added as a display on the vending machine. In this study, the best results were found where all drug inputs issued were in accordance with disease data that had been adjusted to the disease prescription on the RFID tag card.
AI-Powered Interfaces for Extended Reality to Support Remote Maintenance

High-end components that conduct complicated tasks automatically are a part of modern industrial systems. However, in order for these parts to function at the desired level, they need to be maintained by qualified experts. Solutions based on Augmented Reality (AR) have been established with the goal of raising production rates and quality while lowering maintenance costs. With the introduction of two unique interaction interfaces based on wearable targets and human face orientation, we are proposing hands-free advanced interactive solutions in this study with the goal of reducing the bias towards certain users. Using traditional devices in real time, a comparison investigation using alternative interaction interfaces is conducted. The suggested solutions are supported by various AI powered methods such as novel gravity-map based motion adjustment that is made possible by predictive deep models that reduce the bias of traditional hand- or finger-based interaction interfaces.
Preface: 4th International Conference on Educational Reform, Management Science and Sociology (ERMSS 2023)

2023 4th International Conference on Educational Reform, Management Science and Sociology (ERMSS 2023) was successfully held online during January 7-8, 2023 in Detroit, USA. This conference aims to become a springboard for research, innovation and entrepreneur sharing several key technological developments and emerging applications of informatization in education technology, information management, engineering management, business management and public management.&#x0D; ERMSS 2023 invited scholars and experts in related fields from various universities to participate in the review and guidance of this conference. The conference focuses on the latest research fields, and aims to provide an international cooperation and exchange platform for experts, scholars and business managers to share their research achievements, discuss the key challenges and research directions of the development, and jointly promote the industrialization cooperation and continuous innovation of international academic achievements. This collection of proceedings compiles oral and paper presentations submitted by the authors and scrutinized by the special committee.&#x0D; Organizing Committees of ERMSS&#x0D; Detroit, USA
A MODIFIED ALGORITHM FOR MINIMIZING THE DISJUNCTIVE NORMAL FORM

The article describes an algorithm for a directed search to find the minimum disjunctive normal form using the lexicographic order.