Reviewerly/exHarmony huggingface dataset:
Exploring Final Project Trends Utilizing Nuclear Knowledge Taxonomy

The National Nuclear Energy Agency of Indonesia (BATAN) taxonomy is a nuclear competence field organized into six categories. The Polytechnic Institute of Nuclear Technology, as an institution of nuclear education, faces a challenge in organizing student publications according to the fields in the BATAN taxonomy, especially in the library. The goal of this research is to determine the most efficient automatic document classification model using text mining to categorize student final project documents in Indonesian and monitor the development of the nuclear field in each category. The kNN algorithm is used to classify documents and identify the best model by comparing Cosine Similarity, Correlation Similarity, and Dice Similarity, along with vector creation binary term occurrence and TF-IDF. A total of 99 documents labeled as reference data were obtained from the BATAN repository, and 536 unlabeled final project documents were prepared for prediction. In this study, several text mining approaches such as stem, stop words filter, n-grams, and filter by length were utilized. The number of k is 4, with Cosine-binary being the best model with an accuracy value of 97 percent, and kNN works optimally when working with binary term occurrence in Indonesian language documents when compared to TF-IDF. Engineering of Nuclear Devices and Facilities is the most popular field among students, while Management is the least preferred. However, Isotopes and Radiation are the most prominent fields in Nuclear Technochemistry. Text mining can assist librarians in grouping documents based on specific criteria. There is also the possibility of observing the evolution of each existing category based on the increase of documents and the application of similar methods in various circumstances. Because of the curriculum and courses given, the growth of each discipline of nuclear science in the study program is different and varied.
Virtual Production at Cloud901 in the Memphis Central Library

In order to explore the connection between cinematography and graphics programming at Cloud901, I am using my experience in film and programming to develop a “virtual production” initiative in our space. This project serves the purpose of teaching youth how to write programs within Unreal Engine while creating a platform where those interested in the film, programming, music, and visual art aspects of our space can collaborate.
Services to Mobile Users

Libraries are adapting to the changing times by providing mobile services. One hundred fifty-one libraries were chosen based on circulation, with at least one library or library system from each state, to explore the diverse services provided to mobile users across the United States. According to the data, mobile apps, mobile reference services, mobile library catalogs, and mobile printing are among public libraries’ most-frequently offered services, as determined by mobile visits, content analysis, and librarian survey responses. Every library examined had at least one mobile website, mobile catalog, mobile app, or webpage adapted for a mobile device. Following the COVID-19 outbreak, services such as mobile renewal, subscriber database access, mobile reservations, and the ability to interact with a librarian were expanded to allow better communication with customers—all from the comfort and safety of their own homes. Libraries are continually looking for innovative methods to assist their mobile customers as the world changes.
Quantum Coding via Quasi-Cyclic Block Matrix

An effective construction method for long-length quantum code has important applications in the field based on large-scale data. With the rapid development of quantum computing, how to construct this class of quantum coding has become one of the key research fields in quantum information theory. Motivated by the block jacket matrix and its circulant permutation, we proposed a construction method for quantum quasi-cyclic (QC) codes with two classical codes. This simplifies the coding process for long-length quantum error-correction code (QECC) using number decomposition. The obtained code length N can achieve O(n2) if an appropriate prime number n is taken. Furthermore, with a suitable parameter in the construction method, the obtained codes have four cycles in their generator matrices and show good performance for low density codes.
A Contrastive Study on Indonesian and English Question Words

Interrogative sentences constitute one of the most important modes of sentences in any world language. By this type of sentence, the language speakers can get information regarding everything they do not know, something they hesitate, or anything that the hearer wants to agree with. As such, this mode of sentence should be mastered by all language learners. However, like any other mode of sentences, interrogative sentences are also differently structured across languages, bringing serious difficulties for all second language learners. Moreover, languages do not belong to the same family group, like Indonesian, which belongs to the Austronesian family group, and English, which belongs to the Indo-German family group. Concerning this matter, this research paper will briefly describe the differences in the use of Indonesian question words apa, siapa, berapa, di mana, bagaimana,and kapan and its English contrast with what, who, how many/much, where and when. By contrasting Indonesian interrogative sentences containing apa, siapa, berapa, di mana, bagaimana, and kapan, and how they are expressed in English, it is found that not all these Indonesian question words can be directly and translated into what, who, how many/much, where and when. These differences will hopefully enhanche awareness of all language learners about the individualities or peculiarities owned by any language to ease their learning processes.
Iris Classification with Supervised ML using Algorithm of KNN in JavaScript

The Machine learning is what we have to predict the data of unseen nature and gives us predicted results. There are number different machine learning algorithms for prediction and here we will use the supervised machine learning algorithm k-nearest neighbors (KNN) which is used for both the classification and regression analysis problems. In this paper we are predicting the Iris. Iris species are of three types and here we are going to predict that using k-nearest neighbors (KNN) algorithm model with the help of JavaScript.
Rancang Bangun Sistem Informasi Wedding Archive Management pada KUA Sukadiri Tangerang

The Wedding Archive Management Information System at the KUA Sukadiri Tangerang is currently very much needed so that in managing the archiving of wedding document data for Sukadiri residents it can be more organized and easy to find. Previous problems occurred when filing arrangements related to Wedding Archive Management were not properly regulated, causing problems in the form of slow search of the required wedding document data until the data was scattered. The purpose of this study is to design and build a Wedding Archive Management information system for KUA Sukadiri Tangerang so that the arrangements for archiving marriage document data are well organized. This study applies data collection methods, PIECES system analysis methods, system design methods with UML diagrams, Visual paradigm, Black Box Testing, Laravel Framework and PHP programming language. The results of the research are in the form of a Web-based Wedding Archive Management Information System that can search wedding document data in a short time and has been implemented at KUA Sukadiri Tangerang.
Klasifikasi Kendaraan Berbasis Suara Di Lalu Lintas: Implementasi TinyML

Driving is deeply embedded in Indonesian culture. All Indonesian citizens (WNI) who meet the qualifications can obtain a driver's license (SIM). As a result, the number of drivers in Indonesia is relatively significant, resulting in a high rate of traffic accidents. One of the reasons leading to the rising number of road accidents is hearing loss. This study focuses on building a tool that can classify vehicles based on the audio of the vehicle while it is running in order to assist drivers with hearing impairments. This study employs the Arduino Nano 33 BLE Sense, which includes an embedded microphone, and the Edge Impulse open platform. A simple artificial neural network model with four 1-D convolution layers and one hidden layer was utilized. The dataset was obtained manually using the YouTube open platform and was captured directly on the Edge Impulse platform using the Arduino Nano's microphone. The model training procedure was repeated 80 epochs. During training and testing, the model is regarded to be accurate, with accuracy scores of 96.3% and 90.9%, respectively. With these adequate results, the model is judged eligible for implementation, despite the fact that it still requires further refinement.
Multi-recipient and threshold encryption based on hidden multipliers

Let $S$ be a pool of $s$ parties and Alice be the dealer. In this paper, we propose a scheme that allows the dealer to encrypt messages in such a way that only one authorized coalition of parties (which the dealer chooses depending on the message) can decrypt. At the setup stage, each of the parties involved in the process receives an individual key from the dealer. To decrypt information, an authorized coalition of parties must work together to use their keys. Based on this scheme, we propose a threshold encryption scheme. For a given message $f$ the dealer can choose any threshold $m = m(f).$ More precisely, any set of parties of size at least $m$ can evaluate $f$; any set of size less than $m$ cannot do this. Similarly, the distribution of keys among the included parties can be done in such a way that authorized coalitions of parties will be given the opportunity to put a collective digital signature on any documents. This primitive can be generalized to the dynamic setting, where any user can dynamically join the pool $S$. In this case the new user receives a key from the dealer. Also any user can leave the pool $S$. In both cases, already distributed keys of other users do not change. The main feature of the proposed schemes is that for a given $s$ the keys are distributed once and can be used multiple times. The proposed scheme is based on the idea of hidden multipliers in encryption. As a platform, one can use both multiplicative groups of finite fields and groups of invertible elements of commutative rings, in particular, multiplicative groups of residue rings. We propose two versions of this scheme.
Data-Centric Learning from Unlabeled Graphs with Diffusion Model

Graph property prediction tasks are important and numerous. While each task offers a small size of labeled examples, unlabeled graphs have been collected from various sources and at a large scale. A conventional approach is training a model with the unlabeled graphs on self-supervised tasks and then fine-tuning the model on the prediction tasks. However, the self-supervised task knowledge could not be aligned or sometimes conflicted with what the predictions needed. In this paper, we propose to extract the knowledge underlying the large set of unlabeled graphs as a specific set of useful data points to augment each property prediction model. We use a diffusion model to fully utilize the unlabeled graphs and design two new objectives to guide the model's denoising process with each task's labeled data to generate task-specific graph examples and their labels. Experiments demonstrate that our data-centric approach performs significantly better than fifteen existing various methods on fifteen tasks. The performance improvement brought by unlabeled data is visible as the generated labeled examples unlike the self-supervised learning.
A Coordination Mechanism for Parallel Learning between Higher Educational Institutions in Different Countries Worldwide

Educational institutions are a unique system, much more complex than other areas of economic and social life (security, transportation, communications), as it is closely linked to all industries, as well as spiritual and material aspects of both the past and the present. Each country has its mechanism for organizing its educational system. The most powerful initiators of changes in the education system are not its problems or needs but external factors, primarily priorities and requirements for education and upbringing that arise in connection with the country’s inclusion in the common movement of the world community, changes in production, culture, social and security spheres, etc. Therefore, all trends in higher education take into account, on the one hand, the priorities of preserving the cultural diversity of national educational systems and, on the other hand, the tasks of improving international cooperation, student mobility, and employment in the international community. In the course of the research, systemic-structural, comparative, logical, and linguistic methods, analysis, synthesis, induction, deduction, abstraction, and idealization in the processing of scientific information were applied to study and process materials on parallel learning between HEIs around the world. During the research, the most important trends in the study of issues related to parallel learning in higher educational institutions around the world have been outlined. Moreover, based on the questionnaire survey results, the standpoint of university heads and teachers, as well as scholars studying the mechanisms of higher education in different countries of the world, on certain practical aspects have been revealed.
Exploring the Role of English Language Teachers in Developing Reading Habits among Secondary School Students through Libraries

Reading culture enables people to learn, grow, strive for personal betterment, and pursue innovative goals. The school library has a significant impact on its users' love of reading and serves as a source of inspiration. This study sought to understand how the secondary school section's pupils could develop a reading culture through the use of the school library. The goals were to research how secondary school students use the school library to establish their reading habits and how English language teachers can help students develop their reading habits. The network diagram of the variables' conceptual framework served as the study's compass. The research used a descriptive survey methodology. Conveniently, a school was chosen. In addition, 25 English teachers from the school were identified in order to collect information about how they help pupils develop good reading habits. A total of 80 students from secondary schools were employed in the sample, including 80 students chosen using purposive sampling in the Secondary Section. Both open-ended and closed-ended questionnaires were used to obtain the data. It was determined that students used the library to do their projects, do research, and take notes, but they also visited the library at a distinct time slot once a week when they could read and write reviews. English language teachers had a variety of responsibilities, such as encouraging pupils to read; proposing books to librarians from various genres, and helping students create in-class libraries. The conclusion is that because of their exam-focused curriculum, kids don't have enough time for leisure reading. As a result, schools should add more library time to their class schedules to encourage students to develop a reading habit.
Developing a Model of English Digital Poster Book for Teaching English in Indonesia’s Early Childhood Education

Teaching English to Young Learners (TEYL) means introducing English as a foreign language in learning to children. Children should learn a foreign language earlier to expand the boundaries of the world and encourage them to face dynamic international development. Nowadays, children are immersed as native digital users more so than generations past. Therefore, this research is a research and development (R&amp;D) that aims to design, develop and validate an English digital poster book Model teaching English in Indonesia’s early childhood education using the ADDIE Models. This model consists of five steps: analyze, design, develop, implement, and evaluate. The product of this research was developed and then evaluated by four content experts. The result showed that all content experts considered that the final version of an English digital poster book for teaching English in Indonesia’s early childhood education was practical and valid. Based on the observation, most children are excited to use this product in learning English. Teachers also claimed that this product was so interesting, easy to understand, appropriate to the level of difficulty for children in learning English, easy to operate, and can guide them to in teaching English at kindergarten level.
Influence of Blockchain Implementation for Virtual Meetings at Home Learning Indonesia

Online learning is currently one of the popular learning concepts in schools. The results of online learning are still not as expected. This is due to the lack of reliability of teachers in mastering learning platforms and the lack of virtual meetings between teachers and students. Home Learning Indonesia (HLI) is a Learning Management System with virtual meetings and blockchain technology is an alternative to solving this problem. This research utilizes blockchain technology to minimize the shortcomings of existing virtual meeting platforms. In this study, testing HLI virtual meetings and several other platforms. The results of the HLI Virtual meetings test when the requests given are getting higher, and the throughput is decreasing following the number of requests given. These results can show that the use of blockchain in virtual meetings can increase network stability in its use.
Influence of an Immersive Virtual Environment on Learning Effect and Learning Experience

To explore the influence of the immersive virtual environment on the learning process of students, it is necessary to analyze the learning effect and learning experience. The immersive virtual environment provides a new idea for education, changes the traditional teaching mode, adds an immersive experience in the teaching process, and increases the participation and fun of students in the classroom. The learning effect and learning experience were analyzed, the positive effect of the immersive virtual environment on students was verified, and the influence of the immersive virtual environment on learning effect and learning experience was explored. Results indicate that the comprehensive score of teaching effect obtained by students with the research method is higher than that before the use of the research method, before using research methods, the average score of students is 84.7, and the average score of students in the experimental class after adopting the method in this study and one month of learning increases by 10 points. The immersive virtual environment has a positive effect on the learning effect and learning experience of students in each discipline.
Review of Morel and Spector’s (2022) book “Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives” Taylor &amp; Francis

The paper aims to review an important aspect of technology integration in education. The Foundations of Educational Technology: Integrative Approaches and Interdisciplinary Perspectives present various aspects of the foundation of technology in education.
IoT Based Real-Time Weather Monitoring System Using Telegram Bot and Thingsboard Platform

IoT technology's rapid enlargement is implemented in developing automated devices that monitor real-time data. The device design uses the ESP32 Microcontroller, SHTC3 Sensor, BMP180, Windspeed Anemometer, Wind Direction Anemometer, and Tipping Bucket Rain Ombrometer to acquire the current data on weather parameters such as humidity, temperature, altitude, wind speed and direction, air pressure, and precipitation. Using the MQTT, WebSocket, and HTTP Request communication protocols, data transfer from these sensors visualize on the things board dashboard and chatbot telegram. The design of this real-time weather parameter monitoring system integrates with tomorrow's forecasts from BMKG's National Digital Forecast API data. This research carries an axiological approach that contributes to the benefits of the available methods and knowledge to provide more help or value. This research can contribute to the innovation and the development of real-time data observation system automation at BMKG Indonesia as an alternative recommendation to support observation density. In addition, implementing multi-protocol communication in the system can be a scientific reference for the benefits of communication in various outputs.
Study on Artificial Intelligence (AI) in Indian Banking Sector with Special Reference to Punjab National Bank

The meaning of intelligence is the capacity to absorb and learn from experience which can be used as a tool to handle problems and fit into a new situation (Jhangiani et al., 2014). Artificial Intelligence (AI) is the technology that tries to copy logical functions which are prepared by human beings (D’Monte, 2018). In the past two decades, India’s digital banking sector has grown rapidly. The growing number of internet banking, mobile banking and payment app users, are the main catalysts behind the growth of digital banking. The rising demand for online banking has created opportunities for the implementation of AI in the Indian banking sector (Vijai, 2018). The main objectives of the present study are: (i) to discuss the concept of Artificial Intelligence (AI), (ii) to study the implication of AI in the Banking sector and (iii) to state the different aspects of AI in Indian Banking sector with special reference to Punjab National Bank (PNB). AI has played an important role in determining fraudulent accounts and reducing the gross NPA of Banks. The banking operations of PNB had been paralyzed in February 2018 due to fraud carried out by Nirav Modi and Mehul Choksi. After this incident, PNB introduced an AI-enabled audit system to eliminate the loopholes in their banking operations. The Gross NPA of PNB and the total number of frauds reported have decreased by 11.47% and 39% respectively, in the financial year 2021-2022 in comparison to the last year. The present study reveals that day by day, banks are adopting AI for personalized customer services and reducing errors in banking operations. Furthermore, AI can handle NPA Management through Big Data Analytics, which will help in strengthening the balance sheets of banks.
APPLICATION OF CONVOLUTIONAL NEURAL NETWORKS FOR ROAD TYPE CLASSIFICATION

This paper presents an application of convolutional neural networks (CNN) in autonomous driving system, which represents the capacity of a vehicle to operate mostly or entirely autonomously, with or without human assistance. After basic introduction of CNN, we design and apply CNN-based algorithm in road type classification problem. The performed simulations show that satisfactory results can be achieved even with little data available.