Reviewerly/exHarmony huggingface dataset:
A Study of the Analysis of the Blockchain Messaging Apps Market

Distributed ledger and blockchain technologies have revolutionized the way businesses imagine and operate across organizational boundaries. Non-repudiation plays a vital role in communications to overcome disputes and establish trust. The incorporation of blockchain-based messaging enables the usage of a decentralized network of nodes, surmounting the conventional methods. Key market players are emphasizing accessing partnerships with technology-based companies, thereby bolstering its regional demand over the forecast period. This chapter focuses on market analysis and forecasting for the forecast period of 2021–2030 in terms of revenue. Further, the chapter briefly focuses on the determinants such as drivers, restraints, and opportunities impacting the market for blockchain messaging apps in different applications and end-user segments.
Maze Solving Mobile Robot Based on Image Processing and Graph Theory

Advances in the development of collision-free path planning algorithms are the main need not only to solve mazes with robotic systems, but also for their use in modern product transportation or green logistics systems and planning merchandise deliveries inside or outside a factory. This challenge increases as the complexity of the task in its structure also increases. This paper deals with the development of a novel methodology for solving mazes with a mobile robot, using image processing techniques and graph theory. The novelty is that the mobile robot can find the shortest path from a start-point to the end-point into irregular mazes with abundant irregular obstacles, a situation that is not far from reality. Maze information is acquired from an image and depending on the size of the mobile robot, a grid of nodes with the same dimensions of the maze is built. Another contribution of this paper is that the size of the maze can be scaled from 1 m × 1 m to 66 m × 66 m, maintaining the essence of the proposed collision-free path planning methodology. Afterwards, graph theory is used to find the shortest path within the grid of reduced nodes due to the elimination of those nodes absorbed by the irregular obstacles. To avoid the mobile robot to travel through those nodes very close to obstacles and borders, resulting in a collision, each image of the obstacle and border is dilated taking into account the size of the mobile robot. The methodology was validated with two case studies with a mobile robot in different mazes. We emphasize that the maze solution is found in a single computational step, from the maze image as input until the generation of the Path vector. Experimental results show the usefulness of the proposed methodology, which can be used in applications such as intelligent traffic control, military, agriculture and so on.
Real-time psychophysiological approaches to explore emotional and cognitive processing of VR-mediated sports

Purpose The purpose of this research was to investigate how VR-mediated sports, as opposed to 2-D screens, affect the emotional and cognitive experiences of fans with the game and its sponsors. Design/methodology/approach The current study employed a single-factorial experimental design, in which participants were randomly assigned to either watch a soccer game through a VR headset or a 2-D screen. Physiological and self-reported measures were used to measure levels of presence, arousal, attention and memory. Findings Participants who watched sports through VR experienced a higher level of presence, greater psychophysiological arousal, and exhibited higher levels of attention toward the game. However, they showed lower recognition for in-stadium signage compared to those who watched the game on a 2-D screen. Practical implications The results suggest that sports teams can use VR to create a more immersive and engaging experience for fans. Additionally, in-stadium signage advertising may not be as effective in VR sport broadcasting contexts, and sports practitioners may want to explore alternative forms of advertising that are better suited for VR environments. Originality/value Methodologically, this study used a combination of self-reported and real-time physiological measures to capture dynamic and spontaneous changes in fans while watching games. Theoretically, this study utilized the Dynamic Human-Centered Communication System Theory to adopt a human-centered approach to understand how VR impacts the experience of sport game viewers.
KEMAMPUAN AWAL NUMERASI SISWA KELAS V SEKOLAH DASAR DI TUBAN

This study aims to determine the initial numeracy skills of fifth grade students at Tuban. The research subjects were 32 students in class V SD Negeri Kebonsari I and 35 students in class V SD Negeri Kutorejo III. This research is a quantitative descriptive research based on observation and student scores in working numeracy-based questions. The questions given were 10 questions which included multiple choice, true-false, essay, and matchmaking questions. The readings used in the questions are based on local wisdom in Tuban, so it is hoped that students will find it easier to understand. Based on the test results, it was obtained that the average numeracy score of SD Negeri Kebonsari I students was 51 or in the medium category, and SD Negeri Kutorejo III was 14 or in the low category. These results indicate that the numeracy skills of fifth grade elementary school students in Tuban still need to be improved. Therefore, researchers developed thematic books based on local wisdom to improve the numeracy skills of fifth grade elementary school students.
English students’ perceptions about their motivation having online classes during the Covid-19 pandemic

The transition from face-to-face classes to online classes due to the Covid-19 pandemic had a great impact on English Language Teaching students which shaped their opinions about their motivation. For this reason, this qualitative research aims to describe how online classes influenced English students’ motivation during Covid-19 pandemic in a public university in Mexico. Seven students were interviewed. Results showed that students experienced low motivation during the pandemic due to three main reasons: distractions that they had at home, lack of social interaction and lack of feedback. Nevertheless, what kept them motivated was their intrinsic motivation. In contrast, their motivation when having face-to-face classes was higher by far.
Harnessing AI and Big Data for Ethical and Efficient Decisions

Smart technologies like AI and big data have transformed decision-making. These tools are becoming increasingly popular in various businesses, but India's political sector has not used them. The previous two years have seen a pandemic that has impacted society. The chapter investigated whether AI and big data can be used in politics to make faster, more efficient, and morally acceptable decisions, and how politicians can ensure ethical use. Question: How can big data and AI help politicians make ethical decisions? Using relevant literature, the qualitative investigation found utilization, problems, ethical issues, and hazards. Semi-structured interviews with politicians and AI experts were also done to determine if the technologies may be used in politics. Before AI can support decision-making, much political data must be digitized. In conclusion, AI and big data can streamline Indian decision-making through document reading and analysis. There is no ethical framework for AI and big data utilization today, making ethical decisions impossible.
EP095 / #128 REGION-SPECIFIC EFFECTS OF TDCS ON SEMANTIC MEMORY RETRIEVAL

Semantic memory retrieval emerges from the activity of cortical and subcortical brain regions. Yet, it remains elusive how the activity of this brain network implements specific retrieval functions - i.e., the automatic (bottom-up) retrieval of semantically related representations, on the one hand, and the controlled (top-down) retrieval of knowledge, on the other hand.
The English Learning Motivation of Chinese Secondary School Students: Cross-grade Survey Analysis

Existing literature indicates that motivation is the most powerful determining factor that influences the rate and success of second language learning (Jiang, 2016; Kramsch &amp; Yin, 2018; Li &amp; Edwards, 2017; Liu et al., 2016; Liu, 2016; You &amp; Dörnyei, 2016; Zhi &amp; Wang, 2019). Currently, there is a growing body of empirical research indicating the changes in second language learning motivation at different school levels at the same or different schools (Chambers, 1999; Kim, 2011, 2012a, b; Lamb, 2007; Williams et al., 2002). The findings of previous studies have mostly shown that student second language learning motivation increases with increasing school levels. Do¨rnyei (2000) suggested that concentrating on the time dimension of second language motivation is crucial for comprehending the second language motivation of students. However, the temporal variations of second language motivation, particularly motivational changes at different Chinese secondary school levels, have not been emphasized by second language motivation researchers, therefore, this quantitative research investigated the changes in Chinese secondary school students’ English learning motivation from junior high to high school. An English learning motivation questionnaire was used and administered to 3000 students from Grades 7 to 12 in public secondary schools across Mainland China, and employed the reliability analysis and analysis of variance to analyze quantitative data. The statistical results revealed that Chinese high school students ranked highest in English learning motivation, followed by junior high school students. Furthermore, the college entrance examination had a positive impact on high school students' motivation to learn English.
MACHINE LEARNING DETEKSI KANTUK PENGEMUDI MENGGUNAKAN FACIAL NERVE GRADING SYSTEM 2.0 (FNGS2.0) PADA FLATFORM THINKSPEAK

Traffic accidents are one of the negative impacts of technological advances in the field of transportation. The increase in traffic accidents is caused by several factors where the highest factor causing traffic accidents is human/HR. Driver fatigue is a significant factor in a large number of traffic accidents, therefore, to minimize it, an alarm system is needed to detect sleepiness in real time.&#x0D; In this study, a sleepy eye detection system will be made based on Facial Landmarks Detection which is the development of the Facial Nerve Grading System 2.0 (FNGS2.0) using the Eye Aspect Ratio (EAR) and Mouth viewpoint proportion (MAR) methods with the Thingspeak platform which is implemented into Orange Pi PC. The input of this system is video recorded from the webcam in real time. The output of this system uses the speaker as an alarm to give a warning that the driver is detected as sleepy.&#x0D; The system made in this study shows that it can detect sleepy eyes well. The test results show that the system can detect 93.3% of the eyes, 96.7% of eye blinks, and 95% of the mouth.
Models of binary classification of the semantic colouring of texts

Introduction: The purpose of the research is to compare different types of recurrent neural network architectures, namely the long short-term memory and gate recurrent node architecture and the convolutional neural network, and to explore their performance on the example of binary text classification. Material and Methods: To achieve this, the research evaluates the performance of these two popular deep-learning approaches on a dataset consisting of film reviews that are marked with both positive and adverse opinions. The real-world dataset was used to train neural network models using software implementations. Results and Discussion: The research focuses on the implementation of a recurrent neural network for the binary classification of a dataset and explores different types of architecture, approaches and hyperparameters to determine the best model to achieve optimal performance. The software implementation allowed evaluating of various quality metrics, which allowed comparing the performance of the proposed approaches. In addition, the research explores various hyperparameters such as learning rate, packet sizes, and regulation methods to determine their impact on model performance. Conclusion: In general, the research provides valuable insights into the performance of neural networks in binary text classification and highlights the importance of careful architecture selection and hyperparameter tuning to achieve optimal performance.
Mural visual media to enhance environmental caring character of elementary school students

This study aims to describe the use of visual media of mural art in Education to improve the character of environmental care for grade IV elementary school students. The approach used in this study is a qualitative approach or Qualitative Research. The type used in this study is Classroom Action Research to improve the environmental care character of grade IV elementary school students using mural art visual media, carried out in two cycles, each consisting of two meetings with stages of activities including planning, implementation, observation, and reflection, focusing on the use of mural art visual media and character education caring for the environment of students. The study subjects were grade IV B students of Makassar City State Elementary School, totaling 26 students. Data collection techniques are used through educator and learner observation sheets, documentation, tests, and non-tests. The research instruments used are observation sheets and questionnaires used to measure students' character. The data analysis techniques used are qualitative and quantitative data analysis techniques. The research results on character education caring for the environment of students in Cycle I are in the Sufficient category, and Cycle II has increased, namely in the Good category. Based on the study's results, using visual media of mural art can improve character education care for the school environment and the environment around grade IV B students of Makassar City State Elementary School.
Machine learning techniques to predict the risk of developing diabetic nephropathy: a literature review

Abstract Purpose Diabetes is a major public health challenge with widespread prevalence, often leading to complications such as Diabetic Nephropathy (DN)—a chronic condition that progressively impairs kidney function. In this context, it is important to evaluate if Machine learning models can exploit the inherent temporal factor in clinical data to predict the risk of developing DN faster and more accurately than current clinical models. Methods Three different databases were used for this literature review: Scopus, Web of Science, and PubMed. Only articles written in English and published between January 2015 and December 2022 were included. Results We included 11 studies, from which we discuss a number of algorithms capable of extracting knowledge from clinical data, incorporating dynamic aspects in patient assessment, and exploring their evolution over time. We also present a comparison of the different approaches, their performance, advantages, disadvantages, interpretation, and the value that the time factor can bring to a more successful prediction of diabetic nephropathy. Conclusion Our analysis showed that some studies ignored the temporal factor, while others partially exploited it. Greater use of the temporal aspect inherent in Electronic Health Records (EHR) data, together with the integration of omics data, could lead to the development of more reliable and powerful predictive models.
VT-IO: A Virtual Time System Enabling High-fidelity Container-based Network Emulation for I/O Intensive Applications

Network emulation allows unmodified code execution on lightweight containers to enable accurate and scalable networked application testing. However, such testbeds cannot guarantee fidelity under high workloads, especially when many processes concurrently request resources (e.g., CPU, disk I/O, GPU, and network bandwidth) that are more than the underlying physical machine can offer. A virtual time system enables the emulated hosts to maintain their own notion of virtual time. A container can stop advancing its time when not running (e.g., in an idle or suspended state). The existing virtual time systems focus on precise time management for CPU-intensive applications but are not designed to handle other operations, such as disk I/O, network I/O, and GPU computation. In this paper, we develop a lightweight virtual time system that integrates precise I/O time for container-based network emulation. We model and analyze the temporal error during I/O operations and develop a barrier-based time compensation mechanism in the Linux kernel. We also design and implement Dynamic Load Monitor (DLM) to mitigate the temporal error during I/O resource contention. VT-IO enables accurate virtual time advancement with precise I/O time measurement and compensation. The experimental results demonstrate a significant improvement in temporal error with the introduction of DLM. The temporal error is reduced from 7.889 seconds to 0.074 seconds when utilizing the DLM in the virtual time system. Remarkably, this improvement is achieved with an overall overhead of only 1.36% of the total execution time.
Pre-reading Activities: University ESL/EFL Teachers’ Practices and Views

The literature on reading pedagogy has recognized the pivotal role of pre-reading activities in preparing students as readers for the actual act of reading. In this regard, the current paper aimed to investigate University ESL/EFL teachers’ use of pre-reading activities in teaching B.Ed. English major reading courses at a constituent campus of Tribhuvan University. To this end, a case study design was adopted comprising classroom observation and semi-structured interview methods to collect data from four purposively selected English teachers. The findings show personalization of the topic, contextualization of the topic, digging into the title, pre-teaching key vocabulary items, and knowing the author as the most frequently used pre-reading activities. Despite this, students were found to be inadequately engaged in the pre-reading stage for want of variety in pre-reading activities and students’ poor participation. Moreover, coursebook pre-reading activities did not form part of reading lessons for several reasons. Finally, implications are considered for the integration of pre-reading activities for effective reading pedagogy.
PSYCHOLOGICAL AND PEDAGOGICAL ASPECTS OF THE DEVELOPMENT OF VISUAL ACTIVITIES OF PRESCHOOL CHILDREN

The article examines the issues of creativity - as one of the meaningful forms of mental activity of children, as a universal means of individual development, ensuring sustainable adaptation to new living conditions, and as a necessary reserve for an active relationship with reality, both from a psychological and pedagogical point of view. Suggested options for working with children in the field of visual arts.
COMPONENTS OF COMPETENT TRAINING OF SCIENCE TEACHERS FOR SUCCESSFUL PROFESSIONAL ACTIVITIES

The main components of professional competence are revealed in the article. The importance of possessing professional skills and abilities, modern special knowledge of a certain field of production and a high level of professional competence based on crit
THE MAIN SYSTEM COMPONENTS FOR CREATING A METHODOLOGY FOR USING DIGITAL TECHNOLOGIES IN THEIR SCHOOLS

In this work, the main structural components for creating a methodology for using digital technologies in secondary schools are shown, in which the system of principles of teaching using digital technology, the connection of the principles of using digital technology with the principles of classical and informational didactics.
Interactive Vocabulary Learning through VCR (Vocabulary in Contexts and Repetitions) Strategy

Learning English is not merely learning new vocabularies with their meanings in the first language, especially since English is still a foreign language for most of Indonesian students. So, teaching new vocabularies in English do not guarantee proficiency in using English effectively. Therefore, teachers need to think of ways on how to create learning fun and interesting for the students to learn English. Through VCR strategy, teachers involve students to repetitively use the vocabularies learned in different contexts. Teachers need to prepare learning materials and activities that might engage students to use vocabulary in dialogues, songs and movements, stories, and games. Through class observations, interviews, and teaching journals had by 20 English teacher candidates who taught elementary students in a private course in Tangerang, it was found that teaching English vocabulary only was not enough to make students interested in English learning. Unless those vocabularies were taught in real situations as what the students also usually faced in their daily lives, those words will be stored in a short term. The more the students repeated the new words they learned, the more ‘real’ those words in their lives. Teaching vocabularies through contexts that are relevant to the students and repetitions will help Indonesian students learn English easier and more effectively.
FOOD SECURITY POST-PANDEMIC: A COMMUNICATION STRATEGIC OF CATALYST BUSINESS TRANSFORMATION AND INNOVATION

Food is a source of energy to all living beings, as food gives energy through chemical changes that produce ATP (Adenosine Triphosphate) and ADP (Adenosine Diphosphate). Food energy comes in different types of reactions, there are 3 main types of sources of energy carbohydrates, protein, and fat. Meat is one of the main food that many people feed on. This common meat mostly contains mainly protein and fat.&#x0D; This activity is an early step to introduce the scope of performance allocated to companies that will later be appointed to accompany the development of both product and marketing innovation.&#x0D; The product innovations from this activity are revolutionizing the steak industry through dry-aging and home preparation, igniting the grill: innovating the steak experience through T-bone grilling, elevating the burger experience: a novel approach to grilled dry-aged burgers, rediscovering the versatility of top round: a proposal for promoting roasted top round, the sous vide revolution - a twist on traditional boneless beef short ribs, spicy hanger steak pizzaiola; and the marketing strategic communication innovation resulting from this activity is the culinary revival: reimagining recipes with food tech students.
The Methodology of Sherlock Holmes: What Is at the Nub of the Process?

Abstract: The nub of Sherlock Holmes's investigative process has been overlooked in the analytical literature on the subject—until now. This study drills down into the character's methodology to explicate what is at its very heart. I present Holmes as a rational empiricist operating at the explicit level of observation and inference but also as an intuitive empathizer operating at a tacit level of awareness involving imaginative guesswork. I claim that the operational story of the former, where identifying essential clues to resolving a case involves intuitively sensing relevance, necessarily relies on that of the latter.