Reviewerly/exHarmony huggingface dataset:
Real-Time Credit Card Fraud Detection Surveillance System

In this research, the system that detects administrative behavior, credit card and developing corruption from credit cards through LINE applications. The objective of this research 1) To develop a risk notification system or suspect to be corruption of credit cards through the connection channels of LINE application 2) to measure the accuracy of the system developed. As for the notification to prevent the risk of credit card corruption The research methods are divided into 5 steps, namely Step 1, Step System analysis. Is a study and analysis to determine the needs of steps 2 steps, system design Is the process of designing tools used in research. Step 3 System development Is the process of developing the tools used in research. Step 4, the process of testing and correcting the system. Is the process of testing the tools used in research. Step 5 Summary Discuss results and suggestions. The research results are summarized as follows The results of the measurement and completeness of the data are very good as 86.67 percent. The results of the measurement of the correct conditions are as good as 80 percent and the performance measurement of time is in The criteria is as good as 86.67 percent. In conclusion, the corruption system from credit cards through the application alert. LINE can be used appropriately.
Multiplayer Chess Game Development Using Augmented Reality and 3D Models

The principal aim of this project was to innovate the classic board game chess so people can play at any time and place without the need for physical space and real pieces for the game to run correctly. This project can encourage more people to become interested in this board game by using augmented reality technology and personalized models and animations. Players can use the application without the need to use a physical board or pieces and without any kind of image marker. They just need to point at a flat surface with the phone camera so that all the game objects appear and then they can interact with the game intuitively by selecting the elements on the screen. The system has been created to work on high-end Android phones using the technology of Unity and Vuforia.
Comparison of Spelling Error Correction Algorithms for the Indonesian Language

Edit distance as a string measurement metric is often used to help detect misspellings in languages. This paper aims to compare two string spelling error correction algorithms for the Indonesian language. The N-gram, Jaro-Winkler distance, and Levenshtein distance algorithms are used to determine whether they can accurately correct typological errors in the Indonesian language. Moreover, this study utilized KNIME tools to process the data from beginning to end. The data was retrieved from news in Indonesia. After the experiment on N from 1 to 12, the results obtained for the comparative analysis proved that Jaro-Winkler distance performed better than Levenshtein distance for comparing smaller strings like words and names. However, Levenshtein distance performs as well as Jaro-Winkler distance started from four strings. Finally, both Jaro-Winkler distance and Levenshtein distance algorithm got the best performance accuracy for eight strings with an accuracy of 99.52 percent. The result of this study is also presented that both algorithms can support word error correction for the Indonesian language.
A Hybrid Board Game for Learning Blockchain Mechanisms

Blockchain is one of the most significant and innovative technological developments in recent years. Blockchain use cases are no longer limited to the financial sector but have expanded into various industries such as healthcare and education. It is imperative to educate individuals early to prepare them for the widespread adoption of blockchain technology. To this end, we created a hybrid board game to educate players about the blockchain mechanism. The game mechanics incorporate three topics: block properties, mining nodes, and the proof-of-work process. Each player competes to get as many coins as possible from mining and transacting while protecting their mining nodes from other players. This study aims to determine how well the players understood each topic after playing the game. We experimented with 22 students in grades 11 and 12, ranging in age from 17 to 18. We administered a multiple-choice test, followed by an interview, to determine their level of knowledge. After participating in the activity, the average score for the block properties topic was 51 percent, for the mining nodes was 51 percent, and for the proof-of-work process was 40 percent.
DOVAR: Data-on-Object Visualization with Virtual and Augmented Reality in Scientific Education

Virtual and augmented reality is an emerging approach of visualization that provides immersive experience to users. The approach has been widely adopted in different domains such as training, remote conference, navigation, gaming, etc. In education, it has also been widely adopted. For example, the 3D virtual solar system scene has been implemented in multiple applications to help young kids and students to learn basic astronomical knowledge. However, most existing approaches focus on creating virtual objects that simulate real-world objects but on a different scale. In this paper, we propose DOVAR, a novel VR/AR-based visualization approach that visualizes real-time and accumulated data directly on virtual objects. In particular, DOVAR adds data points as colored accessories at different surfaces (i.e. polygons) of the 3D models in a VR or AR environment. Our experiment study on different usage cases shows that visualization technique can be helpful in teaching scientific concepts.
Student Perspective of Online Pedagogy Post COVID-19. A Missed Opportunity?

The COVID-19 pandemic has significantly changed education and caused unprecedented disruptions. These changes may disappear once the schools resume face-to-face classes in full force. Likewise, a positive change may not be necessarily what we want in education. This may be due to the existence of digital divide among students which cannot be ignored. During the COVID-19 pandemic, OneNote Class Notebook is used as an interactive digital whiteboard and has been evident as one of the best alternatives to the traditional whiteboard in the teaching and learning process. In this study, we aim to analyze students’ perceptions of OneNote Class Notebook and the level of their continuous intention to use OneNote Class Notebook as an interactive digital whiteboard to replace the traditional whiteboard when school reopens with face-to-face lessons in the classroom in full force. The findings show that the students perceived that OneNote Class Notebook is indeed a useful tool to be used for calculus learning. But, it cannot be perceived as suitability to continue to be used during post COVID-19 period, when school reopens with physical classes in full force. In this regard, it reminds educators of the importance of rethinking education in the new normal post COVID-19 era from the perspective of curriculum studies.
Development of heat stroke detection system using image processing techniques

This paper presents an approach for a heat stroke detection system by using image processing techniques. In System Design, we use the camera, Web Application, smartphone, and tablet to access the system. In The System Development, the process follows Image acquisition, Image Enhancement, Human Detection, and Temperature Mapping. The experimental results showed that the system can help detect people at risk of heat stroke and can be supported on computer and smartphone platforms. Testing the system with image data from 100 thermal imaging cameras, it was found that the system was 82.5% accurate.
Does Higher Education Need Virtual Reality? A Survey

Interest in virtual reality (VR) is growing steadily, and it is becoming clear that VR can be beneficial in many areas of teaching and learning. There are many studies that have been conducted, didactic models have also been adapted, and there is a wide range of applications, all focusing on VR in education. Besides, there are only a few studies which explore the attitudes, requirements and wishes of teachers and students. It is important to see what lecturers want and what their ideal requirements are. Do they really want to teach in VR? What value do they see in VR? What tools are they already using and how much experience and equipment is available at universities. To answer these questions, we designed a questionnaire encompassing 3 domains with 11 subdomains and a total of 116 questions to explore the requirements, acceptance, and experiences of VR in higher education. Overall, the results (N = 170) show that 50.0% of respondents consider VR important for themselves, but 82.1% believe that VR will be important for practical use in the classroom in the future. Further key findings will be presented and discussed in the paper, and raw data will be made available to the public. In summary, it can be said that the respondents definitely see the benefit and need for VR in higher education, although lecturers and students do not always agree on certain issues.
Teachers’ Perceptions of Videoconferencing and Smartphones in a Retrospective Analysis 2009-2020: An Educational Social Internet of Things Framework

Schools have become increasingly influenced by what has been called the Social Internet of Things (SIoT). As many schools transitioned to online teaching and learning in 2020 because of the COVID-19 pandemic, there is a need to analyze data on technology adoption in schools for changes and continuity since the inception of increasingly popular smartphones since 2007 that has affected videoconferencing, blended learning, and the flipped classroom concept. In this study, videoconference technology is the main factor analyzed in relation to IoT and schools in which handheld devices are considered gateways to further integration of schools into an IoT framework. The researchers analyze a selection of a 2009 dataset and a 2019 dataset from the National Center for Education Statistics (United States) to discuss teachers’ perceptions of technology, especially the use of handheld devices and videoconference technology. Recommendations for educator preparation programs (EPPs) are made based on the discussion of the results of this analysis in context with the events of 2020 for why EPPs could emphasize flipped classroom design models within an SIoT framework.
Enhancing Humanities Learning with Metaverse Technology: A Study on Student Engagement and Performance

This study aimed to evaluate the effectiveness of metaverse technology in education by analyzing the design and setup of virtual environments and comparing flipped and non-flipped classroom methods. The main analysis was conducted through statistical analysis of a survey and text feedback from participants. The results showed that the use of pedagogy in the metaverse was a significant predictor of student intent to use, while technological factors were not. This outcome is contrary to previous studies that have emphasized the importance of technological capabilities in virtual reality education. Feedback and observations also suggested that learning was more engaging when utilizing social interactions with NPCs and offline activities through the flipped classroom method, however, no statistical results were captured for these observations. Additionally, the study found that the use of authoring tools in the metaverse helped in creating and sharing scenes for learning, making it a useful tool for teachers to align their curriculum. Overall, the findings support the potential of metaverse technology to improve student engagement and performance.
Generation Method of Error-Specific Adversarial Examples Using Gradient Information for the Target Class

With the advancement of AI technology, vulnerabilities of AI systems have been pointed out. Adversarial Examples (AEs), in which makes AI wrong decisions, are one of the dreaded attacks for AI. Therefore, a thorough investigation of AEs is essential for the safe use of AI. In this paper, we propose a method for generating adversarial examples using gradient information for the target class of input images. We experimentally prove that the proposed method can generate target AEs that misclassify to an arbitrary class with high probability.
Vocational Students’ Perceptions on the VBee Diary Writing Application: Features and Writing Activity

The research used a qualitative research design to discover the vocational school students’ perspectives on the VBee diary writing application, especially regarding the features and writing activity and whether it could help them improve their writing skills. Purposive sampling was used to select research participants so they could be contacted if additional data were needed. The participants were 117 students who attended three vocational schools on Java Island, Indonesia. Data was also collected through questionnaires and interviews. The findings showed that the features of VBee diary writing, such as emoji and colour, and feedback features were engaging and easy to use, which allowed the students to practice an enjoyable writing activity in English. After that, through the use of the VBee diary writing application, the students thought that they became inventive, expressive, and assured in writing in English. Then, the VBee diary writing application enabled students to improve their writing skills and assisted them in completing teacher-assigned assignments. Furthermore, it was recommended that the VBee’s colour, emoji, and background should be enhanced to make it more engaging. Then, creating an Android version was also strongly recommended so language students as users could log in without first accessing the web and entering their username and password.
Research on the Influence of Embedding Mind Map in 360 Video on Learning Effect

To explore whether embedding a mind map can better support learning in 360 videos, this paper takes 46 college students as the research object. It conducts a single-factor random experiment of "embedding no mind map, embedding concise mind map and embedding detailed mind map in 360 video resources". The results show that embedding a mind map has no significant effect on the primary eye movement behavior, and embedding a concise mind map in 360 videos can promote learners' memory of knowledge. However, at the same time, it will increase cognitive load. The conclusion of this paper can provide a reference for the development of 360 video teaching resources.
Research on Learner Portrait Based on xAPI and Learning Analysis

At present, the deep integration of technology and education has become the focus of researchers. In order to better apply information technology to online learning and provide technical support for personalized learning. This paper constructs learner portrait model from four dimensions: personal information, learning style, behavioral characteristics and learning performance. According to xAPI standard, learning behavior activity flow is designed to collect learning data, extract learning behavior tags and build learner portrait. Finally, the overall analysis and group analysis of learner portrait are carried out with the help of learning analysis, so as to provide personalized and accurate online learning support services for learners and improve learning efficiency and quality.
Remote Teaching-learning Process and Degree of Student Satisfaction in a Private University in Lima, Peru

The objective of this research is to analyze the development of remote teaching regarding its impact on the teaching-learning process and the degree of satisfaction of the students of the School of Law at a private university in Lima, This is a basic research study, with a non-experimental design that describes and correlates the variables "Remote teaching", "Teaching-learning process", and "Degree of student satisfaction", Data collection was done through a virtual-form survey that was completed by a sample of 651 students, The data were processed with SPSS v,25 software for calculating Spearman's Rho coefficient, which made it possible to analyze the correlation between the variables, It was found that there is a significant positive relationship between the "Remote Teaching" variable, and the "Teaching-Learning Process" and "Degree of Satisfaction with the Educational Service" variables, noticing the relevance of the teaching role and the institutional role in achieving a positive perception in students, It was concluded that there is a positive impact of the remote teaching-learning process on the degree of satisfaction of the students participating in the study.
Examining the Association Between Pre-service Teachers’ Self-efficacy and TPACK Competencies in Online Internships Under COVID-19

During the COVID-19 pandemic, pre-service teachers must devote time and effort to familiarizing themselves with the online educational internship system and adapting their pedagogy to the new internship mode that integrates information and communication technologies. Under such a circumstance, teachers’ technological pedagogical content knowledge (TPACK) plays a critical role in making them competent in online internships, and their self-efficacy can facilitate their TPACK development. Based on the data collected from 202 pre-service teachers during the COVID-19 pandemic in China through online surveys, this study investigated the association between their self-efficacy and their TPACK during the online internship. The results of multiple regression analyses suggested that pre-service teachers’ personal and general teaching efficacies significantly predicted TPACK competencies to varying degrees. To be specific, pre-service teachers’ personal teaching efficacy significantly and positively predicted all the TPACK dimensions; meanwhile, GTE only significantly and positively predicted Pedagogical Knowledge (PK), Technological Content Knowledge (TCK), Technological Pedagogical Knowledge (TPK), and Technological Pedagogical Content Knowledge (TPCK). Also, the conclusions, implications, and suggestions for theory and practice were discussed.
Using 360 Virtual Reality Video in History Learning

The use of learning media is an important issue in the current era. The 360-year virtual reality video-based media approach is undeniable topic nowadays. This study aims to explore the initial response related to the 360-degree virtual reality video development product on the topic of history in elementary schools in Indonesia. The first step of the research using ADDIE model for research and development. The second step of this research used a survey method to gather the data. The respondents involved were 102 elementary school teachers in Indonesia. The instrument used was a teacher readiness questionnaire related to VR which showed that 98% of teachers expressed readiness to use VR in learning history material in elementary schools. Further discussions related to the stages of video development are presented in this paper.
[Short paper] Towards improved collaborative text editing CRDTs by using Natural Language Processing

Collaborative text editing systems are used in a variety of cloud-based products. To ensure that documents remain consistent between users, these systems often rely on CRDTs, operational transformation, or other techniques for achieving (strong) eventual consistency. CRDT-based approaches are appealing as they incorporate strategies to ensure that concurrent updates cannot conflict. However, these strategies do not necessarily take into account program semantics and may result in unexpected behaviour from the end-user's perspective.
A Study of Semantics for CRDT-based Collaborative Spreadsheets

Online collaboration is becoming prevalent in our day-today work. As commercial applications show, next to texts, spreadsheets are an essential tool for storing and organizing shared data. However, concurrent modifications of a collaborative spreadsheet can lead to unexpected results when they reflect implementation decisions rather than user intention.
Core sentence vector text matching algorithm based on text classification dataset

With the development of natural language processing technologies such as deep learning and large-scale pre-trained language models, intelligent question answering robots have become more and more popular in industry. The algorithms of text classification and text matching are important for robot automatic response. However, for text classification, the number of categories is always fixed. For text matching, the sentence pairs for training are difficult to collect. In this paper, we propose a novel text matching method to solve the above two problems, which can be trained with only the text classification dataset. The proposed model can have better recognition ability for the newly added appropriate problem categories without retraining. On the basis of pre-trained model, we first conduct further pre-training with contrastive learning, and then conduct multi-task fine-tuning (core sentence vector matching and contrastive learning). The finally obtained model can benefit from both the text classification method and the text matching method.
Quantum-enhanced receiver for quadrature phase shift keying using conjugated homodyne detection

Abstract Coherent detection (homodyne detection/heterodyne detection) and single photon detection are commonly applied in classical communication and quantum communication/receiver respectively. In this paper, we firstly propose a quantum-enhanced receiver based on conjugated homodyne detection, which is consisted of two classical balanced homodyne detectors, for discrimination among quadrature-phase-modulated weak coherent states. Our detection part works as a photon counter in every single-shot measurement during the process of detection and feedback, which could help our quantum-enhanced receiver surpass the standard quantum limit when an optimized detection threshold τ from 0.05 to 0.3 is selected. Moreover, our proposed quantum-enhanced receiver with conjugated homodyne detectors can obtain the same low error probability as conventional quantum-enhanced receivers (with its superconducting nanowire single photon detectors’ detection efficiency 60% for pulse separation $M=8$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>M</mml:mi> <mml:mo>=</mml:mo> <mml:mn>8</mml:mn> </mml:math> and 70% for $M=12$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>M</mml:mi> <mml:mo>=</mml:mo> <mml:mn>12</mml:mn> </mml:math> under the same adaptive feedback countermeasures.) Meanwhile, our scheme of the quantum-enhanced receiver gains its incomparable advantages on room-temperature working condition and low cost due to the application of conjugated homodyne detectors. As far as we concerned, this is the first time to explore the performance of the quantum-enhanced receiver with commercial homodyne detectors. And the analysis in this paper may pave the way to reduce the cost of the quantum-enhanced receiver and make it more adaptable for long-distance optical communication systems.
The Role of Machine Learning in Customer Experience

Machine learning is a subtype of artificial intelligence in which computers use algorithms to learn from data and discover patterns, a capacity that businesses may exploit in various ways to improve customer service. Machine learning (ML) is improving nearly every function and process automation by enabling operational optimisation. As a result, it improves customer service, speeds up work, lessens errors, and improves accuracy. Customer service is one area of the company that might benefit from machine learning. Natural language processing and sentiment analysis are two technologies that can help businesses better understand how to respond to consumer comments and queries.