Reviewerly/exHarmony huggingface dataset:
Augmented Reality Learning Media on Geographic Symptoms to Increase University Students' Knowledge of Geographic Science: Pro-Environmental Behaviour

In supporting difficult learning, innovative learning media are needed. One of the innovative learning media is augmented reality (AR). In this study, there is an AR design that is needed for the material of geographical phenomena. The method used is R D (Borg Gall, 2014). The results obtained in this study are AR designs for geographical phenomena (volcanoes, earthquakes, and tsunamis). It is hoped that the AR design for the material on geographical phenomena in this article can be useful in applying augmented reality material for geographical phenomena in social studies for lecturers who want to develop it as a learning medium for students.
State-Aware Unsafe Driving Action Detection and Defense

Considering most driving accidents are caused by unsafe driving actions, this paper focuses on improving driving safety by proposing a novel state-aware unsafe driving action detection and defense method. By combining three indicators of the vehicle's physical models using fuzzy logic, our approach improves the prediction stability and warning time without sacrificing false alarm rates. This research enhances vehicle cybersecurity and contributes to safer and more secure transportation systems.
PECULIARITIES OF MODERN PERSONNEL MANAGEMENT IN THE HOTEL AND RESTAURANT INDUSTRY

Innovative educational technologies: European experience and its application in training in economics and management : Proceedings of scientific and pedagogical internship (February 13 – March 26, 2023, Riga, Latvia). Riga, Latvia : “Baltija Publishing”, 2023.
FeatGeNN: Improving Model Performance for Tabular Data with Correlation-Based Feature Extraction

Automated Feature Engineering (AutoFE) has become an important task for any machine learning project, as it can help improve model performance and gain more information for statistical analysis. However, most current approaches for AutoFE rely on manual feature creation or use methods that can generate a large number of features, which can be computationally intensive and lead to overfitting. To address these challenges, we propose a novel convolutional method called FeatGeNN that extracts and creates new features using correlation as a pooling function. Unlike traditional pooling functions like max-pooling, correlation-based pooling considers the linear relationship between the features in the data matrix, making it more suitable for tabular data. We evaluate our method on various benchmark datasets and demonstrate that FeatGeNN outperforms existing AutoFE approaches regarding model performance. Our results suggest that correlation-based pooling can be a promising alternative to max-pooling for AutoFE in tabular data applications.
The importance of training in social organizations’ due to COVID-19 pandemic challenges

This work presents the grounding behind ongoing research. In the face of the COVID-19 pandemic, declared by World Health Organization, being the Residential Structures for the Elderly confined, the workers in solitary confinement, and the elderly without any visits, we started this research which aims to assess the effects of online training and activities, mainly on reducing the stress levels of workers and elderly, the loneliness feeling among the elderly, and the workers’ engagement. Using technologies, and with the contributions from a multidisciplinary team, we built some resources to minimize the pandemic effects in seniors and workers of Residential Structures for the Elderly. All the materials were placed in a document repository created for the purpose, so they could be accessed whenever necessary, especially at a time that could ease the heavy task experienced by workers in these structures and when it was possible to accompany the residents, as some tasks require assistance and instruction in their accomplishment. The research project team, which has been running since March 2020, intends that in 2021 this project becomes a virtual resource center, available for all national social organizations, after carrying out all the proposed and verified changes by the analysis of the protocol built for this purpose. This project will be a repository for good practices, offering a set of tools and activities, recorded and in real time, available for all the organizations in the social sector, but above all for most isolated and with the least economic resources.
Geography in the context of the New Ukrainian school

The purpose of the article is to study the Geography of the educational field «Natural Science» in the New Ukrainian school. Main material. The new Ukrainian school is a supernova phenomenon in the Ukrainian scientific world, which began its «life» in 2017. It is based on nine components and ten key competencies. According to the current State standard of basic and complete general secondary education, «Geography» is a component of the educational fi eld «Natural Science». Its purpose is to form in pupil’s natural science competence as basic and relevant subject competencies, a mandatory component of the general culture of the individual and development of his creative potential. Geography, in the vision of the New Ukrainian School, is knowledge of the natural fi eld of education. Its purpose is to form the personality of a pupil who knows and understands the basic laws of animate and inanimate nature, has certain skills of its research, shows curiosity, realizes the integrity of natural-scientific picture of the world. The pupil is able to assess the impact of natural sciences, machinery and technology on the sustainable development of society and possible consequences of human activities in nature, responsibly interacts with the natural environment. The geographical component involves formation of basic knowledge on the following issues: geography as a science; the role of geographical education in human life; Land on a map; geographic information systems. Moreover, there are other components as well: Earth as a geosystem, levels of geosystems; geographical consequences of parameters and movements of the Earth; geo-graphical shell; anthroposphere; relationship of processes in the lithosphere, hydrosphere, atmosphere, biosphere, natural complexes; resource potential of the Earth’s crust, modern aspects of its use; global problems of humanity. Conclusions and further research. A comparison of the geographical component content of the educational fi eld «Natural Science» in accordance with the current State Standard of Basic and Complete General Secondary Education (2011) and the State Standard of Basic Secondary Education adopted in 2020 shows that the new document contains a much narrower content of modern geographical science. In particular, the geographical component does not provide for the formation of pupils’ basic knowledge on important issues of regional physical and social geography. Further research aims to build and justify the optimal model of the pupils’ geographical competence of a modern institution of general secondary education.
Developing English Project Based Learning Supplementary Materials for Computer and Network Engineering Vocational High School

This research has been conducted with the aims to develop an English supplementary material in the form of e-module for reading skill difficulty in Computer and Network Engineering VHS students. The difficulty in reading made the students cannot understand the matter given easily. Moreover, in Kurikulum Merdeka, reading skill becomes one of focused skill to improve the literacy aspect. This study was Research and Development (R&amp;D) which used ADDIE model. Questionnaires were used for collecting data in preliminary study, expert validations after the product developed, and students’ perception after trial product. While the researcher used the field note to gather document analysis result and interview guidelines as structured interview instrument to English teacher. All expert validation result showed &gt;74,99%. The media expert had been on 95%, the matter expert was on 75%, and the final score from linguistic expert was on 95%. The student’s perception questionnaire had been on 84% with positive responses which reached “Good” category. Whereas the validation and reliability final counting are &gt;0.457 and 0.815 which defined as valid and reliable. The e-module can be used as supplementary material for English teaching especially in Vocational High School.
THE PROBLEM OF THE FOUNDATIONS OF SCIENTIFIC RATIONALITY&#x0D; IN THE CONTEXT OF COGNITIVE PRACTICES OF EVERYDAY&#x0D; CONSCIOUSNESS

The 20th century and the beginning of the 21st century were marked by the&#x0D; deontologisation of the language of science, the dominance of the attitudes of epistemological&#x0D; naturalism, the loss of the truth’s absolute value and the purpose of cognition, and as a&#x0D; consequence, the unprecedented increase in the relevance of rethinking mathematics and&#x0D; mathematical natural science (physics, biology, etc.) in terms of everyday consciousness&#x0D; and everyday experience. This work is connected with the necessity to clarify the boundaries&#x0D; of identity and differences between the formations of sensory-visual experience and the&#x0D; products of abstract-theoretical construction, the intuitive and the logical-discursive,&#x0D; explanation and understanding, the theoretical and the empirical, etc., in the context of&#x0D; the analysis of the deriving oppositions and counter-views as expressions of opposites of&#x0D; reflexive and non-reflexive “layers” of consciousness in structures of cognitive and vitalpractical activity
Towards object tracking for quadruped robots

With the development of quadruped robot technology, object tracking for quadruped robots has become an important research topic where violent camera shaking caused by the robot’s movement makes this task very challenging. In this letter, a quadruped robot object tracking dataset (QROD-111), including 111 video sequences, is first established, which was collected through our quadruped robot platform. A tracking algorithm based on Siamese network is then proposed where an alignment module is introduced to alleviate tracking difficulties caused by the quadruped robot movement. Moreover, a scale adaptation subnetwork is designed to alleviate the impact of the object scale variation during the whole tracking process. Experimental results demonstrate that our algorithm can achieve advanced performance for quadruped robot object tracking.
A Novel Architecture for Robust and Adaptive Machine Learning Using Heterogeneous Data in Condition Monitoring of Automation Systems

Machine learning implementations in an industrial setting poses various challenges due to the heterogeneous nature of the data sources. A classical machine learning algorithm cannot adapt to dynamic changes in the environment, such as the addition, removal, or failure of a data source. However, to handle heterogeneous data and the challenges coming with this, it is a mandatory capability to build robust and adaptive machine learning models for industrial applications. In this work, a novel architecture for robust and adaptive machine learning is proposed to address these challenges. For this, an architecture consisting of different modular layers is developed, where different models can be easily plugged in. The architecture can handle heterogeneous data with different fusion techniques, which are discussed and evaluated in this paper. The proposed architecture is then evaluated on two public datasets for condition monitoring of automation systems to prove its robustness and adaptiveness. The architecture is compared with baseline models and shows more robust performance in case of failing/removed data sources. In addition, new data sources can easily be added without the need to retrain the whole model. Furthermore, the architecture can detect and locate faulty data sources.
PREDIKSI JARAK TEMPUH KAPAL MOTOR SANGIANG MENGGUNAKAN SUPERVISED MACHINE LEARNING

As a maritime nation with thousands of islands and a vast sea area, sea transportation is the most effective transportation used by the people of Indonesia. A motorboat is one type of maritime transportation that is used to move people or commodities. In this article, we will discuss predicting the daily mileage of one of the motorboats, the Sangiang, which travels from Bitung to Ternate. Three independent variables, Anchor Time (minutes), Speed (knots/hour), and Sailing Time (minutes), are used in supervised machine learning techniques to estimate the daily mileage (mile). Of the various methods evaluated, the multiple regression model was found to be the most accurate at forecasting the Sangiang motorboat’s daily mileage.
Adaptive Drum Kit Learning System: Impact on Students’ Learning Outcomes

Computer technology is increasingly integrated into various teaching and educational processes. The role of various educational tools and artificial intelligence in the educational process is becoming more and more significant for overall educational success. In this paper, a review of the scientific literature on the application of computer technology for music education is given, with an emphasis on learning to play musical instruments. It has been observed that for many created systems, proper evaluation was not conducted to determine the created systems’ effectiveness in achieving desired learning outcomes. An innovative part of this paper is a description of a new conceptual model of an adaptive system for self-paced learning to play musical instruments. A prototype of an adaptive drum kit learning system has been created based on the presented model. The main goal of this research was to determine the effectiveness of created prototype in achieving students’ learning outcomes. In the evaluation process, the use of created prototype was compared to other self-paced learning methods to learn how to play the drum kit. The obtained data were analyzed by ANOVA method, along with other appropriate statistical methods. The results of the research showed that the use of an adaptive drum kit learning system has a positive impact on achieving learning outcomes. The participants who learned to play using the created prototype were more precise in playing, played more accurate rhythmic patterns, and were rated with higher marks by an independent expert compared to the control groups. Based on the obtained results, it can be concluded that there is a potential for the application of computer technology in the process of learning to play musical instruments.
Human-Computer Interactive Digital-Twin System Driven by Magnetic-Inertia Fusion Data

As the basic interface for human-computer interaction, human hand allows us to operate digital devices in a natural and intuitive way. With the advent of touch screens, gestures and other forms of gesture recognition technology, the role of the hand in human-computer interaction has become even more important. From mobile devices to game consoles, virtual reality systems to industrial systems, it enables us to quickly manipulate objects and perform complex tasks that are difficult to achieve with traditional input devices. In this paper, we develop a digital twin system based on magnetic inertial data driven data glove, and build a personalized 3D virtual hand model in Solidworks. Import Simulink through the United Robotics Description Format (URDF) plug-in. Then Simscpae Multibody is used to drive the virtual hand model in real time. The simulation results show that the virtual finger model obtained by the inverse solution of magnetic positioning can follow the human hand to complete the corresponding action under the interface of Simulink, and the real-time performance is good.
A hierarchical image matching method for incremental SFM

Since feature matching of image pairs brings a heavy computational burden, Structure-from-Motion faces great challenges in efficiency, especially for unordered large-scale image collections. To solve it, we propose a hierarchical image matching method in this paper. Our approach starts with an iterative image retrieval scheme, which can efficiently find potentially overlapping image pairs as candidates and avoid unnecessary computation. Then, feature extraction, feature matching and geometric verification are implemented in candidates to find the verified image pairs and inlier feature correspondences. Experiments on benchmark datasets and large-scale unordered datasets demonstrate that our method performs competitiveness in efficiency, without degrading the accuracy, compared with the state-of-the-art system.
Wavelet sets, scaling sets and generalized scaling sets on Vilenkin group

Wavelet sets provide a range of wavelets that can be analyzed with ease. The constructions of wavelet sets and scaling sets in different settings are studied in several papers in the literature. Wavelet sets provide a good source of examples and counterexamples in wavelet theory. In this paper we have studied properties of (multi)wavelet sets and associated wavelets for Vilenkin group. Further, results related to scaling sets and generalized scaling sets are given along with some characterizations.
Avatar Customization, Personality, and the Perception of Work Group Inclusion in Immersive Virtual Reality

Virtual reality (VR) has experienced exponential growth in attention in the past five years. Many see it as a new communication mechanism through which people can come together in a way they have never been able to via traditional online interfaces. However, much is still unknown about how VR may affect how groups of users communicate. In this work, we present preliminary findings on how avatars, the customization choices users make to create them, and user perception of them may affect feelings of work group inclusion. We study this in the context of a formal classroom setting with work groups comprised of students. Avatars are known to transform user perception and behavior in virtual environments – both immersive and non-immersive – and can dictate the way social interactions play out in these scenarios. We produce results that align with this paradigm, showing that elements of work group inclusion are different between the physical world and VR, and that customization choices and user perceptions of avatars may shape the perception of inclusion.
The Functions and Characteristics of Emojis and Memes in Intimate Interpersonal Online Communication

Emojis and memes have become prevalent in digital communication, particularly in intimate online chatting. This research analyzes the use of emojis and memes in intimate online chatting through the lens of rapport management theory, with a focus on two questions: 1) What are the characteristics of emojis and memes used in intimate online communication? 2) What are the functions of emojis and memes used in intimate online communication? Using ethnographic methods, data is collected from an online chatting group called “Siblings in law,” which consisted of four members. Our findings revealed three characteristics of emojis and memes used in intimate online chatting: 1) Emojis are used more often than memes, but memes are preferred by online interlocutors. 2) Different individuals have different preferences for emojis and memes, and they use emojis or memes that their friends like to use. 3) The same emoji used in a different context may convey different or even opposite meanings. Additionally, we found that emojis and memes in intimate online communication serve three functions: 1) They protect the face of interlocutors by upgrading praise and downgrading ordering utterances. 2) They help realize the association principle of the rapport management theory. 3) Certain types of emojis and memes assist in achieving the interactional goal of intimate online communication.
The emergence of quantum energy science

Abstract Quantum engineering seeks to create novel technologies based on the exploitation of distinctly nonclassical behaviors such as quantum coherence. The vast majority of currently pursued applications fall into the domain of quantum information science, with quantum computing as the most visible subdomain. However, other applications of quantum engineering are fast emerging. Here, we review the deployment of quantum engineering principles in the fields of solar energy, batteries, and nuclear energy. We identify commonalities across quantum engineering approaches in those apparently disparate fields and draw direct parallels to quantum information science. We find that a shared knowledge base is forming, which de facto corresponds to a new domain that we refer to as ‘quantum energy science’. Quantum energy science bears the promise of substantial performance improvements across energy technologies such as organic solar cells, batteries, and nuclear fusion. The recognition of this emerging domain may be of great relevance to actors concerned with energy innovation. It may also benefit active researchers in this domain by increasing visibility and motivating the deployment of resources and institutional support.
Optimization of intelligent recommendation of innovation and entrepreneurship projects based on collaborative filtering algorithm

The advent of the information age has made accurate search for information a challenge. In this paper, we analyze intelligent recommendations for innovative entrepreneurial projects based on collaborative filtering algorithms. Collaborative filtering is one of the most widely used and successful techniques in recommendation systems. In this paper, an interest migration function plus time is introduced to address the shortcomings of traditional collaborative filtering recommendation algorithms. Meanwhile, this paper builds an intelligent recommendation engine system for innovative entrepreneurial projects based on the Hadoop open-source distributed computing framework, sustainable PSCM, and Mahout collaborative filtering recommendation engine technology. This paper uses experiments to test and evaluate the overall performance of the distributed recommendation platform and the improved collaborative filtering recommendation algorithm. It is found that the algorithm outperforms similar algorithms in terms of data volume and coverage of recommended innovation and entrepreneurship projects. This is sufficient to show that the collaborative filtering algorithm and sustainable PSCM are useful for the intelligent recommendation analysis of innovative entrepreneurial projects.