Reviewerly/exHarmony huggingface dataset:
THE PROBLEM OF ORGANIZING VOLUNTEER ACTIVITIES TO PROVIDE A SAFE EDUCATIONAL ENVIRONMENT FROM THE PERSPECTIVE OF A HEALTHY LIFESTYLE OF STUDENT YOUTH

The well-being of citizens, encompassing their psychological health and adherence to a wholesome lifestyle (HLS), assumes a pivotal role in steering societal rejuvenation, modernization, and transformation. This is particularly vital for nurturing the younger generation and catalyzing the construction of New Kazakhstan, propelling its ascent to the ranks of the world's most developed nations. The presented article emerges from the context of a scientific project with the core objective of delving into the mechanics of orchestrating volunteer initiatives and furnishing scientific and methodological support. The central focus resides in cultivating a psychologically secure educational milieu that champions healthy lifestyles for young individuals within the vocational education system. The paramount relevance and societal gravitas of this issue have enabled the authors to delineate pathways to enhance the training of future teacher-psychologists. The spotlight of this enhancement is cast on the orchestration of volunteer activities that underpin a secure educational environment conducive to fostering healthy lifestyles among young learners. The efficacy of this ongoing endeavor emanates from its multi-pronged approach: a meticulous alignment of developed materials with regional nuances; a concentrated effort on cultivating practical proficiency in the application of health-preserving technologies; and a deliberate emphasis on fostering synergistic collaborations between educational institutions and community support structures. The yield of this rigorous exploration, coupled with scientifically grounded recommendations, serves as a guiding compass for educational managers and instructors within higher and secondary vocational education domains. These insights illuminate pathways for formulating educational programs, crafting elective courses at higher and postgraduate levels, shaping the preparation of bachelor's, master's, and doctoral candidates in the realm of psychological and pedagogical studies. Moreover, they also underpin the creation of advanced training modules tailored for educators in universities and colleges.
STRUCTURAL-SUBSTANTIVE MODEL OF FORMATION OF PEDAGOGICAL CREATIVITY OF FUTURE TEACHERS OF COMPUTER SCIENCE

Socio-economic development in society reflects the high demand for a creative person who can successfully solve problems and change their behavior. Modern conditions increase the need for active, business-minded, creative professionals who are able to move forward and solve various problems on their own in non-standard situations. To be confident in the face of constant change, a future computer science teacher must activate his or her creativity and help students discover their potential and focus on solving the problem. The social demand for education is determined by the needs of the state, society and social groups. In this regard, the social order for creative people capable of creativity, striving for innovation and scientific achievements, non-standard, original thinking makes the issue of formation of pedagogical creativity of future computer science teachers relevant. The purpose of the structural and content model of the formation of pedagogical creativity of future teachers of computer science is to form their ability to pedagogical creativity: the student's understanding of the meaning and content of pedagogical creativity; aspiration of the student to the formation of pedagogical creativity. Creativity and innovation are an integral part of the learning process and the basis of all disciplines. They are an important aspect of how to teach in the process. In addition, creativity and innovation are crucial for teachers who are improving their professional skills. In terms of creativity, teachers play an important and key role in universities, as they provide organizational support for innovation and creativity in the teaching process. The high level of creativity of teachers contributes to the development of students - to increase their competence and demand in the labor market. However, if there is a big difference between the high level of creativity of the teacher and the low level of perception of students, the high creativity of the teacher has a negative impact. In addition, factors that may have a negative impact are: irrationalism on one or both sides; lack of constructivism, low level of communication skills of the teacher; lack of feedback in the learning process, etc. The considered world trends in the development of education are general. In addition, there are new trends in the development of different types and levels of education, depending on their goals, characteristics, the nature of implementation and the new social requirements for the level of training of relevant graduates.
The Use of Virtual Whiteboards in the Process of Teaching Biological Disciplines

The article deals with one of the urgent problems of our time – the possibility of implementing the educational process remotely. In order to present modern approaches to the organization and conduct of the educational process using information and communication technologies between the teacher and the student in the educational process, a list of available virtual whiteboards was presented, an analysis of their advantages and disadvantages was carried out. The article focuses on the ways of adaptive use of virtual whiteboards in the process of teaching biological disciplines. The authors draw attention to the possibility of using the Padlet virtual whiteboard when conducting biological disciplines based on a trilingual education system. The article provides practical recommendations for creating an online Padlet board, for using the ZOOM platform features as a whiteboard. The authors point out that the Padlet virtual whiteboard has a number of advantages and can be effectively used both during science lessons and after school hours. The authors note that virtual whiteboards should not be used as a place to demonstrate educational materials, but as a joint space that allows creating a common educational product with students attending classes remotely, increasing their participation in the educational process. Considering that the use of an interactive online whiteboard is an integral part of the modern educational process, the authors conclude that the Padlet virtual whiteboard is a technologically ideal option.
Biofeedback-Driven Multiplayer Games: Leveraging Social Awareness and Physiological Signals for Play

This paper proposes the formalisation of social awareness as a design dimension for multiplayer biofeedback-driven games. The CHI Play community has shown a growing interest in exploring the potential of biofeedback and physiological sensing for playful experiences and player-computer interaction. Building on existing multiplayer games that integrate biofeedback for play in the literature, we demonstrate how awareness complements existing multiplayer game design dimensions (mode, setting) and further propose research and design directions to advance this area of study.
Stackable Music: A Marker-Based Augmented Reality Music Synthesis Game

Augmented reality (AR) allows the rendering of digital content on top of the physical space, which is a promising medium for tangible interaction. Marker-based AR is widely used thanks to its low cost and ease of integration, but the gameful aspect of manipulating the physical AR markers remains understudied. In this paper, we explored the stacking mechanics of transparent AR markers and described the creation of an AR music game called Stackable Music. Stackable Music can be developed, assembled, and set up at the home or office with a printer using several sheets of transparent film and a PC or mobile device with a camera.
Developing Your Software Engineering Career: Words of Advice From Seasoned Professionals

This special issue of IEEE Software includes ten feature articles on career development in software engineering.
A Practical Guide to Autoscaling Solutions for Next Generation Internet Applications

With the increasing opportunities offered by the cloud continuum (with the availability of distributed edge cloud nodes in addition to traditional datacenter nodes) and the associated growing complexity of distributed virtualized deployment environments, it is often not trivial to statically select the best autoscaling solution to optimally manage resource elasticity for a specific application and for its requirements. In addition, for example because the traffic to a next generation Internet application in the cloud continuum may be highly variable, there is the need of a high degree of adaptability to dynamically determine the best tradeoff between the usage of virtualized resources and its cost. The paper aims at providing a practical guide to the state-of-the-art of autoscaling technologies by describing, comparing, and evaluating them. In particular, we propose an original taxonomy to classify and label the most promising and emerging autoscaling technologies. This taxonomy allows us also to define criteria and practical guidelines on which autoscaling solution to select and integrate in next generation cloud continuum applications, and sheds some light on the most promising directions expected for future research work to fill the current technology gaps.
Pengaruh Penggunaan Media Pembelajaran Flash Card pada Materi Sistem Pencernaan Manusia terhadap Hasil Belajar

This study aims to determine how student learning outcomes on the material of the human digestive system class XI SMA Al Munawwir Tamban use flash card media. The design of this study used a pre-experimental research design with the type of One-Group Pretest-Posttest Design. The sample in this study used one class of 16 students. The treatment in this class is divided into two, namely by using flash card media and not using flash card media. The instrument given is in the form of a test instrument which consists of 30 multiple choice questions. The results showed that in the t-test the t-table value was 2.131, thus the t-count value was 15.800&gt; 2.131, then the t-count value with t-table, it can be concluded that H0 is rejected and H1 is accepted, which means that there is an average difference between the pretest learning outcomes. with posttest, which means that there is an effect of using flash card media on Biology learning outcomes in class XI SMA Al Munawwir Tamban. Keywords: Flash card, learning outcomes.
3D Object Detection in Autonomous Driving

3D object detection is an important perception module in autonomous driving systems. It recognizes sensor observations and predicts locations, sizes and orientations of key objects, which provides both semantic and spatial information for high-level decision making. In this chapter, we first introduce and analyze the properties of commonly used perceptual sensors in autonomous vehicles: cameras, LiDARs and RADARs. Then we define the research problem, detail the assumptions and introduce evaluation metrics of 3D object detection in the context of autonomous driving. The main body reviews the state-of-the-art techniques and categorize them into camera-based, LiDAR-based, RADAR-based and multi-sensor fusion methods. For each method, we point out the main problems and their existing solutions. By analyzing the limitations of existing methods, we propose promising directions and open problems for future research.
Feasible Sentiment Analysis of Real Time Twitter Data

Sentiment analysis plays a significant role in understanding public opinion, trends, and sentiments expressed on social media platforms. In this paper, we focus on performing sentiment analysis on real-time Twitter data to gain insights into the sentiments related to specific topics or events, we collect a stream of tweets based on predefined keywords or hashtags. The collected tweets undergo pre-processing steps to clean and standardize the text for sentiment analysis. We employ machine learning classify the sentiments expressed in tweets, utilizing sentiment lexicons and training data as references. Real-time sentiment analysis is performed as new tweets are collected, enabling continuous monitoring and analysis of public sentiment. The sentiment analysis results are visualized through informative visualizations such as sentiment distribution charts and sentiment trends over time. Additionally, we focus on topic-specific analysis by filtering tweets based on relevant keywords or hashtags, providing deeper insights into sentiments related to specific subjects. The paper faces challenges such as noisy and informal text, ambiguity in sentiment expression, and handling large volumes of real-time data. Addressing these challenges, we aim to develop an effective sentiment analysis system that provides valuable insights into public sentiment and supports decision-making processes in various domains.
The Perception of Information Communication Technologies (ICTs) and Organizational Support among Extension Workers in Nigeria.

The study assesses the perception of ICTs and organizational support among extension workers in North central Nigeria. Data were collected through the use of a questionnaire to 291 respondents, simple random sampling method was employed. Mean, frequency, standard deviation, correlation coefficient, and Multi-linear regression were used for data analysis. Findings reveal a moderate level of ICTs training, high level of ICTs application and moderate level of Perceived organizational support. Based on result from the Bivariate correlation, the result revealed a positive and significant correlation between ICTs application (r=0.309) and job performance at P&lt;0.01. The findings indicated that, among all the variables used in the multi linear regression based on the stepwise method ICTs training, work experiences explained 37%, 58% respectively Quantity work while only about 47% ICTs training and 48% perceived organizational support explained Quality of work. ICTs training and Perceived organizational support was also able to explained 43% and 45% Speed of work respectively.
Introducing Fundamental Types of Data

In this chapter, we’ll explain the fundamental data types that are built into C++. You’ll need these in every program. All the object-oriented capabilities are founded on these fundamental data types because all the data types that you create are ultimately defined in terms of the basic numerical data your computer works with. By the end of the chapter, you’ll be able to write a simple C++ program of the traditional form: input – process – output.
How much, what and how: three-dimensional discourse analysis of Saudi women and men's self-disclosure

Purpose The purpose of this paper is to examine the behavior of self-disclosure among Saudi women and men in an attempt to understand gender differences in language. The study also gives insights about the cultural norms and how they affect language production. Design/methodology/approach The author utilized Levi-Belz and Kreiner's (2019) three-dimensional tool of self-disclosure; namely, the HOW MUCH dimension, the WHAT dimension and the HOW dimension. The HOW MUCH dimension is measured through word count of self-disclosure and the duration of self-disclosure in spoken discourse. The WHAT dimension is measured through analyzing the topics, emotions and social actors that are discussed during self-disclosure episodes. The HOW dimension is measured through examining the acoustic features of self-disclosure such as intonation, loudness and fluency. Findings Saudi women tend to engage in more self-disclosure than Saudi men, and their self-disclosure tends to be longer and more detailed. Women also tend to use more intonation variability and softer loudness, reflecting the cultural norms of politeness and reservation. Both genders tend to use similar frequencies of positive and negative emotion words in their self-disclosure, with positive emotion words correlating more with personal self-disclosure and negative emotion words with self-disclosures about loss, failure, conflict, rejection and uncertainty. The data also show that the use of reflective verbs leads to more authentic and empathetic communication and that pronoun use correlates with the type of emotional experience being discussed. Research limitations/implications This study has limitations due to a small sample size. Future research should use larger and diverse samples to explore self-disclosure in Saudi televised interviews comprehensively. The study focused solely on televised interviews; future research can examine self-disclosure across various media platforms. Findings have practical implications for Saudi media and policymakers. Understanding self-disclosure in interviews can guide content creation, fostering open communication. Presenters consciously act as role models, influencing Saudi youth, emphasizing the role of positive self-presentation. Originality/value This study utilized Levi-Belz and Kreiner's (2019) three-dimensional tool of self-disclosure in a way that could be used for other languages and cultures. The study examines the Saudi cultural norms in self-disclosure, which has never been tackled before.
THE CURRENT STATE AND WAYS TO IMPROVE THE QUALITY OF TRAINING OF SPECIALISTS IN THE SPECIALTY "ECOLOGY" AT POLTAVA V.G. KOROLENKO NATIONAL PEDAGOGICAL UNIVERSITY

The article deals with the state of higher environmental education at V.G. Korolenko Poltava National Pedagogical University. The stages of formation of the (bachelor's) level of higher education in the specialty 101 "Ecology" are highlighted. The priority directions of professional development of teachers of natural sciences are analyzed. The ways to improve the quality of training of environmental specialists at the Poltava V.G. Korolenko National Pedagogical University are considered. It has been found that the university creates and provides mechanisms for comprehensive educational, organizational, informational, advisory and social support for students during their studies. Communication and support for students of the educational program is carried out at the following main levels: higher education student ‒ teachers; curators; university services; student self-government bodies. Communication is carried out directly (communication during classroom classes, in the framework of writing term papers and qualification papers; in the preparation of various events, etc.) and indirectly (providing access to educational and information materials on the University's web resources; access to the library repository; creating groups in social networks, etc.). This structure of communication between the participants of the educational process allows for the implementation of educational and informational (exchange of educational, scientific, educational and methodological information; transfer of socially significant norms and values), organizational (coordination of joint actions, feedback between the subjects of interaction), advisory (clarification of certain issues arising within the educational process) and social (providing support, motivating students) functions.
ViFi-Loc: Multi-modal Pedestrian Localization using GAN with Camera-Phone Correspondences

In Smart City and Vehicle-to-Everything (V2X) systems, acquiring pedestrians’ accurate locations is crucial to traffic and pedestrian safety. Current systems adopt cameras and wireless sensors to estimate people’s locations via sensor fusion. Standard fusion algorithms, however, become inapplicable when multi-modal data is not associated. For example, pedestrians are out of the camera field of view, or data from the camera modality is missing. To address this challenge and produce more accurate location estimations for pedestrians, we propose a localization solution based on a Generative Adversarial Network (GAN) architecture. During training, it learns the underlying linkage between pedestrians’ camera-phone data correspondences. During inference, it generates refined position estimations based only on pedestrians’ phone data that consists of GPS, IMU, and FTM. Results show that our GAN produces 3D coordinates at 1 to 2 meters localization error across 5 different outdoor scenes. We further show that the proposed model supports self-learning. The generated coordinates can be associated with pedestrians’ bounding box coordinates to obtain additional camera-phone data correspondences. This allows automatic data collection during inference. Results show that after fine-tuning the GAN model on the expanded dataset, localization accuracy is further improved by up to 26%.
TongueTap: Multimodal Tongue Gesture Recognition with Head-Worn Devices

Mouth-based interfaces are a promising new approach enabling silent, hands-free and eyes-free interaction with wearable devices. However, interfaces sensing mouth movements are traditionally custom-designed and placed near or within the mouth. TongueTap synchronizes multimodal EEG, PPG, IMU, eye tracking and head tracking data from two commercial headsets to facilitate tongue gesture recognition using only off-the-shelf devices on the upper face. We classified eight closed-mouth tongue gestures with 94% accuracy, offering an invisible and inaudible method for discreet control of head-worn devices. Moreover, we found that the IMU alone differentiates eight gestures with 80% accuracy and a subset of four gestures with 92% accuracy. We built a dataset of 48,000 gesture trials across 16 participants, allowing TongueTap to perform user-independent classification. Our findings suggest tongue gestures can be a viable interaction technique for VR/AR headsets and earables without requiring novel hardware.
AIUnet: Asymptotic inference with U2-Net for referring image segmentation

Referring image segmentation aims to segment a target object from an image by providing a natural language expression. While recent methods have made remarkable advancements, few have designed effective deep fusion processes for cross-model features or focused on the fine details of vision. In this paper, we propose AIUnet, an asymptotic inference method that uses U2-Net. The core of AIUnet is a Cross-model U2-Net (CMU) module, which integrates a Text guide vision (TGV) module into U2-Net, achieving efficient interaction of cross-model information at different scales. CMU focuses more on location information in high-level features and learns finer detail information in low-level features. Additionally, we propose a Features Enhance Decoder (FED) module to improve the recognition of fine details and decode cross-model features to binary masks. The FED module leverages a simple CNN-based approach to enhance multi-modal features. Our experiments show that AIUnet achieved competitive results on three standard datasets.Code is available at https://github.com/LJQbiu/AIUnet.