Reviewerly/exHarmony huggingface dataset:
A BIT of Protection for Non-Fungible Tokens: Digital Assets as a Catalyst for Economic Growth

Abstract An inevitable consequence of technological advancement is that it triggers regulatory challenges for law and policymakers. The regulation of digital assets has generated much debate in this regard. The central objective of this article is to examine the regulation of one particular type of digital asset, NFTs, through an international investment law lens. The international investment regime offers investors high levels of protection against breaches of obligations by host states for covered investments. The aim of the article is to determine whether NFTs can be considered as covered investments for the purposes of the application of bilateral investment treaties (BITs) and treaties with investment provisions (TIPs), and further to examine whether that regime would provide an appropriate regulatory framework for investment in NFTs.
Assessment Of Witness Testimonials As Evidence In Civil Cases

The purpose of this study is to investigate and explain the judge's judgment of witness testimony as evidence in the judge's decision. The study employed a normative legal research technique with primary legal sources. In accordance to the author, this judge's reasoning is incorrect due to the fact that there is an oral agreement between the plaintiff and the defendant, which is confirmed by testimony from witnesses and expert witnesses, it cannot be classified as a breach of contract because it does not meet the requirements set forth in Article 58 of the Indonesian Civil Code. The rules and regulations of Article 58 of the Indonesian Civil Code are coercive legal provisions (dwingend recht). Article 58 of the Indonesian Civil Code contains three conditions: 1. The vows of marriage must be registered in the civil registry; 2. Civil registration officials must declare the marriage plans on the notice board; and 3. Claims/lawsuits must be filed within 18 months of the marriage announcement. The judge's assessment that the defendant had broken his vow was incorrect. As a result, the participation of the witness in providing information in collaboration with other witnesses cannot be used to prove the marriage commitment.
How does AI create and recommend corresponding wallpapers based on the games played by users?

The purpose of this paper is to give a comprehensive review of the related work that has everything to do with creating a wallpaper in artificial intelligence (AI) technology. Firstly, deep learning and neural network are summarized, especially generative adversarial networks that aim to effective generate images. Then, User interest modeling is summarized and analyzed, which is a key point to figure out the preference of the players. Further, main ideas are given about the trends and directions of wallpaper generation by AI.
Research on autonomous mobile robot maze navigation problem based on Dijkstras algorithm

In recent years, the field of autonomous mobile robotics has garnered significant attention due to its potential applications in various domains such as logistics, surveillance, and search and rescue operations. A crucial challenge in this area is the efficient navigation of robots within complex and dynamic environments, particularly when navigating through maze-like structures. The maze navigation problem involves finding optimal paths for robots to traverse from their initial positions to designated destinations while avoiding obstacles and making intelligent decisions to ensure timely and safe navigation. This study aims to investigate and apply Dijkstras algorithm to solve the maze navigation problem for autonomous mobile robots. By analyzing the navigation challenges faced by autonomous mobile robots in maze environments, a solution based on Dijkstras algorithm is proposed. In conclusion, this study contributes to the field of autonomous mobile robotics by proposing and evaluating the application of Dijkstras algorithm for maze navigation. The experimental results validate its potential to address the challenges of navigating intricate maze environments. However, it is acknowledged that further refinement and innovation are possible to continue improving the performance of autonomous mobile robots in maze navigation scenarios.
Multimodal human-computer interaction for virtual reality

Virtual reality (VR) is an interactive simulation environment based on computer technology that enables users to immerse themselves in a virtual world. With the continuous advancement of technology, VR has shown great potential in various fields. This article aims to review the application of VR in different fields and its impact on society. First, this paper introduces VR's basic principles and technical characteristics. VR systems are usually composed of head-mounted display devices, trackers, joysticks, etc., enabling users to experience immersive virtual environments by simulating real-world perception and interaction. Secondly, this paper discusses the application of VR in the field of education. VR technology can provide an immersive learning experience, enabling students to personally participate in the course content, greatly enhancing the effect of learning. At the same time, VR can also simulate experimental scenes, train operational skills, etc., to provide students with more abundant and practical learning resources. Then, this paper introduces the application of VR in the medical field. VR can be used for rehabilitation training of patients, psychological treatment, and other aspects, effectively improving the quality and effect of medical services. In addition, this paper also discusses the application of VR in entertainment, tourism, and other fields. VR technology can bring users immersive gaming experience, virtual tourism, etc., and inject new vitality into the entertainment industry. In tourism, VR can provide tourists with an immersive sightseeing experience, so they can feel the distant scenery at home.
The evolution of transformer models from unidirectional to bidirectional in Natural Language Processing

Transformer models have revolutionized Natural Language Processing (NLP), transitioning from traditional sequential models to innovative architectures based on attention mechanisms. The shift from unidirectional to bidirectional models has been a remarkable development in NLP. This paper mainly focuses on the evolution of NLP caused by Transformer models, with the transition from unidirectional to bidirectional modeling. This paper explores how the transformer model has revolutionized NLP, and the evolution from traditional sequential models to innovative attention-driven architectures. In this paper, it mainly discusses the limitations of traditional NLP models like RNNs, LSTMs and CNN when handling lengthy text sequences and complex dependencies, highlighting how transformer models, employing self-attention mechanisms and bidirectional modeling (e.g., BERT and GPT), have significantly improved NLP tasks. It provides a thorough review of the shift from unidirectional to bidirectional transformer models, offering insights into their utilization and development. Finally, this paper concludes with a summary and outlook for the entire study.
Performance dispersion among target date funds

Abstract There are significant differences in the performance of Target Date Funds (TDFs) with the same target year. Using a unique dataset from Morningstar, we show that within the same target year, funds with lower than the average expense ratio, or higher than average allocation to equities, outperform similar funds. This outperformance exists across all target year groups and is economically meaningful. Furthermore, deviations in the equity allocation have a greater impact on performance than does expense ratio. Using bootstrap simulations to investigate the impact over a longer horizon, we show that deviations from the average allocations or expense ratios have a meaningful impact on the retirement savings of an average investor.
Analysis of -ary tree algorithms with successive interference cancellation

Abstract We calculate the mean throughput, number of collisions, successes, and idle slots for random tree algorithms with successive interference cancellation. Except for the case of the throughput for the binary tree, all the results are new. We furthermore disprove the claim that only the binary tree maximizes throughput. Our method works with many observables and can be used as a blueprint for further analysis.
Impact of Dataset Scaling on Hierarchical Clustering: A Comparative Analysis of Distance-Based and Ratio-Based Methods

In this study, the distance-based agglomerative hierarchical clustering techniques were compared to a ratio-based approach. Two real datasets, which were also used in a prior study by Roux (2018), were considered. Firstly, it was observed that the type of scaling applied to the datasets was found to affect the results of hierarchical clustering. Thus, various scaling methods were employed prior to implementing hierarchical clustering. Furthermore, two rank-based goodness-of-fit measures were used to evaluate the hierarchical clustering methods. In contrast to Roux (2018) findings, it was observed that the distance-based methods, such as Median linkage, Average linkage, and centroid linkage, performed better than the ratio-based method. The ratio-based methods also showed issues with branch crossing in the hierarchical clustering dendrogram. Consequently, this study illustrates that, with appropriate dataset scaling, the distance-based methods outperform ratio-based methods in terms of goodness-of-fit measures.
SiamFDA: feature dynamic activation siamese network for visual tracking

Abstract In this paper, we present a novel anchor-free visual tracking framework, referred to as feature dynamic activation siamese network (SiamFDA), which addresses the issue of ignoring global spatial information in current Siamese network-based tracking algorithms. Our approach captures long-range dependencies between distant pixels in space, which enables robustness to unreliable regions. Additionally, we introduce a hierarchical feature selector that adaptively activates features at different layers, and an adaptive sample label assignment method to further improve tracking performance. Our extensive evaluations on six benchmark datasets, including VOT-2018, VOT-2019, GOT10k, LaSOT, OTB-2015, and OTB-2013, demonstrate that SiamFDA outperforms several state-of-the-art trackers in various challenging scenarios, with a real-time frame rate of 40 frames per second.
Analysis of pre-service teachers' flow experience in educational drama practices and the effect of practices on attitudes toward creative drama courses

Aim: The analysis of the flow experience of pre-service teachers in educational drama practices and the effect of the practices on the attitude towards creative drama lessons reveal the purpose of the study. It is of great importance for physical education teachers to use creative drama practices as an effective teaching method in physical education and sports lessons, both in terms of their personal development and professional development. Method: The study was designed with a pre-test-post-test control group experimental design, one of the true experimental designs, and one of the quantitative research methods. In addition to the demographic information form, the "Flow Experience Scale" and "Attitude Scale towards Creative Drama Lessons" were applied to the participants as measurement tools. The distribution of the participant's demographic information was analyzed by frequency analysis. T-test independent groups analyzed the participants' pre-test and post-test scale scores, and the change in the pre-test and post-test scores of the scales according to demographic information was analyzed by t-test in independent groups and one-way analysis of variance. A regression model was tested to determine the effect of reason on anxiety. Analyses were performed with SPSS 20.0 software at a 95% confidence level. Findings and Conclusions: As a result, there was no significant difference between the attitude scale scores towards flow experience and creative drama course of the students participating in the research according to their age, gender, income level, place of residence, and activity type, and between the pre-tests and post-tests of the scales. However, a significant difference was detected between the pre-test and post-test scores of the flow experience scale anxiety sub-dimension and the flow sub-dimension of the academic achievement variable. In addition, although there was no significant difference in terms of the variables mentioned, it was noted that the flow experience flow and anxiety subscale scores were low. In contrast, the attitude scores towards the creative drama course were high.
Content Modeling in Multi-Platform Multilingual Social Media Data

An increase in the use of social media as the primary news source for the general population has created an ecosystem in which organic conversation commingles with inorganically seeded and amplified narratives, which can include public relations and marketing activity but also covert and malign influence operations. An efficient and easily understandable analysis of such data is important, as it allows relevant stakeholders to protect online communities and free discussion while better identifying activity and content that may violate social media platform terms of service. To accomplish this, we propose a method of large-scale social media data analysis, which allows for multilingual conversations to be analyzed in depth across any number of social media platforms simultaneously. Our method uses a text embedding model, i.e., a natural language processing model that holds semantic and contextual understandings of language. The model uses an “understanding” of language to represent posts as coordinates in a high-dimensional space, such that posts with similar meanings are assigned coordinates close together. We then cluster and analyze the posts to identify online topics of conversation existing across multiple social media platforms. We explicitly show how our method can be applied to four different datasets, three consisting of Chinese social media posts related to the Belt and Road Initiative and one relating to the Russia-Ukraine war, and we find politically-influenced conversations that contain misleading information relating to the Chinese government and the Russia-Ukraine war.
Penerapan Model Pembelajaran Berbasis Maslah Untuk Meningkatkan Hasil Belajar Siswa Kelas XI Pada Materi Hukum Pascal

Research on the problem based learning model on Pascal's law material aims to determine student learning outcomes in class XII. This research is classroom action research that uses Kurt Lewin's model or method. Kurt Lewin's classroom action research model consists of several stages, namely planning, action, observation and reflection. In this research, two cycles of research were carried out. Model based learning is often called problem based learning. By providing problems, it is hoped that students can be active in searching for and finding solutions to the problems given. With problem-based learning, educators try to invite students to be active in learning activities. Based on the results of data analysis, it was found that this learning experienced an increase in the percentage of learning completion and an increase in the class average. So the percentage of students who do not complete has decreased. The data results in cycle I showed that student learning completeness was 82.35% and in cycle II it rose to 88.48%. In cycle II the average student score was 76.47 and in cycle II the average student score rose to 85.25%. Meanwhile, the percentage of student failure to complete in cycle I was 17.65% and in cycle II it decreased to 11.52%. From the data results it can be concluded that the use of model based learning in Pascal's law material for class XII students can improve student learning outcomes.
An Analysis of Narratives on Vocational Consignment Education Experience of Students in General High Schools

The purpose of this study is to understand in-depth the context of the situation and the subjective meaning composition in the selection of vocational consignment education, the life process, and the process of returning to school and adaptation after the interruption, focusing on the experience story that constitutes the personal and social life of students who experience vocational consignment education in general high schools. Therefore, this study examined the selection and life process of vocational consignment education and the process of returning to school and adaptation after the interruption of consignment education by using narrative analysis method for the stories directly dictated by students of vocational consignment education in general high schools. The results of this study are as follows: First, the choice of vocational consignment education for general high schools considers one's aptitude and talent, and the interaction with the surrounding people and the composition of one's meaning play a very important role in the difference of the choice decision. Next, in the career consignment education life of general high schools, it was found that there was a great psychological and emotional reward that strengthened career awareness by having a sense of accomplishment or confidence due to the pride of preparing for the desired job in accordance with the aptitude and talent of the students, the support of the teacher, and the learning success experience coming from the consignment curriculum. However, there was a case where students in the consignment educational institution did not form a sense of identity or belonging properly. In addition, psychological and cultural factors such as the burden and difficulty of acquiring practical training and certification, the sense of heterogeneity felt in the collective culture among the consignment education students, the difficulties in communication and exchanges with the consignment education participants, and the reconsideration of their interests and interests through consignment education and the turning of their career goals to college were the complex factors that determined their return to school after the interruption of consignment education.
USE OF SONG MEDIA IN LEARNING AS AN EFFORT TO INCREASE STUDENTS' LEARNING MOTIVATION ON THE SUBJECTS OF SCIENCE

This Best Practice writing aims to describe the use of song media to improve students' understanding of the material taught by the teacher. The subjects of this Best Practice writing were 25 students in class IV A of Wirasakti Atambua State Elementary School, West Atambua District. Writing this Best Practice uses a descriptive method. The achievement of Best Practice activities is 100%. This is because all activities have been carried out and the output obtained is in line with expectations. The use of song media to increase student motivation towards the material taught by the teacher is effective. The results of the implementation of Best Practice that have been implemented are: 1). Learning activities using song media related to the material studied every day are effective. 2). The use of song media in learning really helps students' understanding of the material being taught because it can be sung repeatedly both in class and at home. 3). Based on the learning that has been carried out, differences can be felt between students who carry out learning using song media and using the lecture learning model. 4). The activities that have been designed in the RPP (Teaching Module) can be implemented fully in accordance with what has been planned. The increase in students' understanding of the material being taught can be seen from the achievement of student learning outcomes, through the results of the pre-test and post-test that have been carried out by the teacher, where in the pre-test of the total number of students in class IV A, only 7 students or 2.24% who are able to achieve the KKM value. Meanwhile, in the post test results, there was a significant increase, namely 25 students, 7 students or 2.24% achieved the KKM score and 18 students or 92.8% were able to achieve a score above the KKM score.
Prolegomena about the cluster-network model organization of the educational system in musical academies of Ukraine

The article „Prolegomena about the cluster-network model organization of the educational system in the musical academies of Ukraine” discusses the complexity of higher musical education and the need for new scientific approaches to address the changing pedagogical reality. The authors propose a cluster-network model for organizing the educational system in musical academies, which is based on the following components: conceptual – tasks, methods, forms, means; axiological– values; psychological and pedagogical – mechanisms of learning values; organizational and management – management of elements of the educational structure. The cluster-network model aims to increase the competitiveness of the educational system by developing the students’ competencies that meet the requirements of the social order. It also emphasizes the importance of spirituality in education and the need for a holistic approach to human development. The authors argue that the ideal of human education is constantly changing, but the ability to correlate the concepts, ideas, and theories acquired during cognitive activity with an individual value system is a key indicator of successful education. The article highlights the importance of understanding the inner class and spiritual being of a person, as well as the need to implement some methods that contribute to penetrating into the phenomenological secrets of human consciousness for researching and revealing the most important mental structures of man. It also discusses the role of dialogue as a way of existing and coexisting- with the „other” in the communication process. The proposed model aims to address the challenges of the postmodern era, where the world is thought of as an open text not limited in its manifestations and interpretations. It emphasizes the importance of continuous education and the integration of knowledge from related disciplines to develop digital education and innovative work practices.
Six miniatures for violin and piano by A. Mulear: analytical references

Alexandr Mulear - one of the prominent and profoundly original personalities of the local music culture, has been prodigiously active over the years in the field of musical creation, leaving a portfolio that abounds in notable works, substantially contributing to the enrichment of the interpretive repertoire. The genres approached by the composer are diverse and extend over a vast compositional area. However, a major proportion of the highlighted works are instrumental works with cyclical forms. Six Miniatures for Violin and Piano is one of the works that marks the stage of the master’s interest in compositional experimentation. In this article, we propose some keys for decoding the form, language, compositional aspects, reception and valorization of A. Mulear’s music through the prism of the analyzed work.