Reviewerly/exHarmony huggingface dataset:
Application of Deep Learning Models for Bone-Conducted Speech Signals Extracted in the Form of Bone Conduction Headphones

In this study, we used deep learning to align bone-conducted speech signals with air-conducted speech signals, aiming to replace traditional air conduction microphones in voice-based services capturing surrounding sounds. We fabricated headphones, placing bone conduction microphones on the rami (the branches of a bone in the jaw area), in line with traditional bone conduction headphone configurations. Using LSTM, CNN, and CRNN models, we created databases that aligned bone-conducted speech signals with their air-conducted counterparts and tested them with bone-conducted speech signals captured via our custom-made headphones. The CNN model demonstrated superior performance in accurately distinguishing three English words (“apple,” “hello,” and “pass”), including their voiceless pronunciations. In conclusion, our study shows that deep learning models can effectively use bone-conducted speech signals extracted from the rami for automatic speech recognition (ASR), paving the way for future ASR technology that precisely recognizes only the speaker’s voice.
Attribute-specific Cyberbullying Detection Using Artificial Intelligence

Cyberbullying, a pervasive issue in the digital age, poses threats to individuals’ well-being across various attributes such as religion, age, ethnicity, and gender. This research employs artificial intelligence to detect cyberbullying instances in Twitter data, utilizing both traditional and deep learning models. The study repurposes the Sentiment140 dataset, originally intended for sentiment analysis, for the nuanced task of cyberbullying detection. Ethical considerations guide the dataset transformation process, ensuring responsible AI development. The Naive Bayes algorithm demonstrates commendable precision, recall, and accuracy, showcasing its efficacy. The Bi-LSTM model, leveraging deep learning capabilities, exhibits nuanced cyberbullying detection. The study also underscores limitations, emphasizing the need for refined models and diverse datasets.
COVID-19 e aspectos psicossociais e econômicos na população brasileira

Objective: This study aimed to identify the psychosocial and economic characteristics of people affected by COVID-19 and their support network at the beginning of the pandemic. Methods: We conducted a cross-sectional study of 2,702 people aged 18 and over living in Brazil. Google® Forms were used to develop an online questionnaire containing open- and closed-ended questions about sociodemographic, economic and health characteristics. Results: People dissatisfied with their health and those who showed emotional changes were more likely to need support (PR=1.74; p&lt;0.001 and PR=2.39; p&lt;0.001). Support from family members stood out [536 (70.2%)]. Bivariate and multivariate analysis showed statistically significant associations of COVID-19 infection with sociodemographic and economic aspects, such as age (p&lt;0.001); region of the country (p&lt;0.001), marital status (p=0.003), number of people per household (p=0.003), employment status (p=0.012), holding a health insurance (p=0.014), needing some other type of support (p&lt;0.001) and not being satisfied with current health status (p=0.043). Conclusion: The findings indicate that COVID-19 negatively affects satisfaction with health and influences the need to seek some type of social support.
Design of an educational strategy based on digital resources for the teaching of social sciences

This research proposes a pedagogical strategy incorporating digital tools for teaching Social Sciences. A quantitative approach is employed data collection targeting educational authorities, teachers, and students to assess the commitment and feasibility of implementing a new educational proposal. The results reflect the commitment and interest of participants towards creating this pedagogical strategy. Various digital tools are suggested, including Telegram for communication, ChatGPT and Virtual Encyclopedias for content generation, Kahoot and Google Form for assessment, and Timeline JS and Powtoon for dynamic presentations. Finally, the proposal was validated through a comparative study between a control group and an experimental one. The findings indicate that the new pedagogical strategy offers a higher innovation, relevance, and improvement in students' learning process.
ANALYSIS OF THE NEEDS OF MANDARIN TEACHING USERS ON LIVE STREAMING PLATFORMS

The rapid development of live streaming platforms has attracted an increasing number of knowledge sharers and learners. These platforms have expanded from entertainment and live commerce to knowledge sharing and monetization. Mandarin Chinese teaching has gained popularity due to its vast user base and relatively low teaching threshold. However, after a period of practice, some drawbacks have been observed, impacting teaching effectiveness and students' learning outcomes. Through questionnaires, specific student needs will be identified, and collaborative efforts among the platform, regulatory authorities, and content providers will be undertaken to improve and enhance Mandarin Chinese teaching on live-streaming platforms. This paper employs quantitative analysis to investigate the distribution of Mandarin learners on live streaming platforms, factors influencing their learning, and their satisfaction levels with the learning process. The aim is to provide valuable insights for future Mandarin teaching on live-streaming platforms and other educational domains. The rapid development of live streaming platforms has attracted increasing knowledge sharers and learners. These platforms have expanded from entertainment and live commerce to knowledge sharing and monetisation. Mandarin Chinese teaching has gained popularity due to its vast user base and relatively low teaching threshold. However, after a period of practice, some drawbacks have been observed, impacting teaching effectiveness and students' learning outcomes. Through questionnaires, specific student needs will be identified, and collaborative efforts among the platform, regulatory authorities, and content providers will be undertaken to improve and enhance Mandarin Chinese teaching on live-streaming platforms. This paper employs quantitative analysis to investigate the distribution of Mandarin learners on live streaming platforms, factors influencing their learning, and their satisfaction levels with the learning process. The aim is to provide valuable insights for future Mandarin teaching on live-streaming platforms and other educational domains.
Exploring the Levels of Undergraduate University Students' Study Skills

The ability to study well is crucial to students' academic performance. The aims of this research were to investigate the study skills levels of undergraduate students, to determine the correlation between academic performance and the study skills of undergraduate students, and to identify any noteworthy variations in study skills based on gender and location. Multi-stage stratified random sampling technique was used to select representative sample of 2207 undergraduate students from Punjab, Pakistan's general public universities. With the author's consent, a modified version of the study skills evaluation questionnaire was adapted, and the academic performance scale was created, verified, and subjected to a reliability coefficient of .094 and 0.85. Four research hypotheses were developed and put to the test using the t-test, Pearson r, mean, and standard deviation. The results indicated a substantial difference in terms of gender and location, as well as a favorable link between study skills and academic performance. Moreover, the majority of undergraduate students employed study skills at a moderate level; therefore, it is recommended to design and incorporate study skills in educational courses for students in academic curricula.
Reconstructing near-water-wall temperature in coal-fired boilers using improved transfer learning and hidden layer configuration optimization

The temperature field is a critical factor for ensuring the safe combustion and energy conservation in boilers. However, an effective method for reconstructing the temperature field near the water wall is still under exploration. In this paper, a method for online reconstruction of the temperature field distribution near the water wall in a 330 MW tangentially fired coal boiler is proposed, which progresses from a well-established model for the entire furnace. A two-branch fusion network for transfer learning (TBFN-TL) method is proposed, incorporating additional key parameters, heat flux, during the transfer process to enhance the effectiveness. A Bayesian hierarchical neural architecture search (BHNAS) method is proposed to optimize the configuration of the hidden layers in building neural networks. Compared with computational fluid dynamics (CFD) results, the mean absolute percentage error (MAPE) of the reconstruction results for the entire furnace model, traditional transfer learning methods, and the proposed TBFN-TL are 11.57%, 5.738%, and 2.052%, respectively, demonstrating a significant enhancement. The proposed BHNAS method extends the search optimization space, obtaining more excellent configurations for the hidden layer nodes. The proposed methods have significant implications for temperature field reconstruction, the field of transfer learning, and the optimization of hidden layer configurations.
Optimizing Disaster Response: OptiDrone- Advanced Integration of Dijkstra's Algorithm and Cutting-Edge Software Solutions for UAV Path Planning and Obstacle Avoidance Efficiency

The objective of the research is development of a specific concept called "OptiDrone," which is based on the integration of Dijkstra's Algorithm and the latest development of aerial vehicles' path planning and obstacle avoidance efficacy. The study involves a combination of theoretical and algorithmic refinement as well simulation-based experiments to test the effectiveness of OptiDrone in dynamic disaster scenarios. OptiDrone's combination of powerful route planning techniques along with advanced software programs is set to achieve a substantially higher response rate and operational resilience in the face of difficulties. The results add much value to the body of knowledge about UAV-assisted disaster management systems, indicating possible gains in efficiency and timeliness while addressing crisis situations. Different disciplines of disaster management, robotics, and software engineering can benefit from this research, which is a significant milestone towards the use of more efficient and innovative unmanned aerial systems in disaster response.
FOSTERING LITERACY SKILLS IN KINDERGARTEN THROUGH PROJECT-BASED POP-UP BOOK CRAFTING

This study is an experimental research aimed at determining the influence of project-based pop-up book creafting on literacy skills. The population in this study consists of all kindergarten children in the city of Makassar. The research sample was selected using a probability sampling technique, and the selected kindergartens were Teratai UNM Kindergarten with 15 children and Ceria Kindergarten with 15 children. The study analyzes findings using descriptive analysis techniques and Independent-sample T-test. The results showed that the average post-test score of students who participated in project learning in the creation of pop-up books increased to 83.52, while students who participated in conventional learning reached 66.48. The hypothesis test results showed that the t value was 5.486 with a significance of 0.000, confirming a highly significant difference in literacy skills between the groups that followed project-based learning and conventional learning. Therefore, based on the research findings, improving literacy skills in children requires attention to the learning model used, ensuring that the provided learning activities are suitable and capable of stimulating child development.
A Building Model for Enhancing Information Systems Security

Today, electronic systems and information have become no less important than food and water for human life. No one can deny this fact. Electronic information systems contribute to the development of life in many areas. But some electronic information systems should not be available for anyone to use, such as reading, operating, modifying or destroying without permission. This type of electronic information systems must be protected in some way based on the related situation. . Password-based authentication is the first defense for most information systems. Password security enhances the security of the entire information system. Therefore, password protection models become very important in such cases to help users improve authentication security. Researchers published various methods based on salting, hashing, symmetric encryption, and key splitting methods. The paper conducted by Saleh Al-Asali describes a method for generating a suitable secret key that is easy to memorize and remember, as he succeeded in generating a password that is strong and easy to remember. This paper improves the previous method by adding some improvements mentioned in the section described in the suggested method.
Needs Analysis for Education for Students with Health Impairments

As the number of students with health impairments continues to increase and the need for customized educational support increases, interest in education for students with health impairments is increasing. This study explored deeply and comprehensively the development tasks in education for students with health impairments to solve current issues and response to educational changes. In specific, the needs of all subjects(public officials, teachers, teachers of consigned educational institutions, students, and parents) related to education for students with health impairments were investigated through focus group interviews. As a result of the study, a total of 10 needs related to the curriculum and contents, educational methods and evaluations, student and teacher support, and the new educational policies were identified, and we found that each need was closely related. Each need derived from this research explains the development tasks for the education of students with health impairments and the necessity of establishing a role for each subjects.
Analysis of early childhood teachers’ climate change teaching capabilities using IPA technique

This study examined the importance and implementation of climate change teaching competencies for early childhood teachers. An IPA analysis was conducted to examine the priorities of educational content to strengthen early childhood teachers' climate change teaching capabilities. For this study, questionnaires were distributed and collected online to early childhood teachers working in kindergartens in Chungcheongbuk-do and Gyeonggi-do. The final research subjects sampled were 51 people. As a result of this study, looking at the difference between the current level and importance of early childhood teachers' climate change response practice competency and ecological citizenship competency, there was a significant difference. The importance of overall climate change response capabilities and ecological citizenship capabilities was higher than the current level. And looking at the results of the IPA analysis of early childhood teachers' climate change response practice capabilities, the strengthening and maintenance of teaching capabilities was found to be the will to implement climate change and climate change sensitivity. The capacity that requires intensive management was found to be the ability to reflect on climate change. According to the IPA analysis results among early childhood teachers' teaching competencies on ecological citizenship, the competency that required intensive management was participation, and the competency that required gradual improvement was justice. Through the results of this study, climate change teaching capabilities necessary for early childhood teachers were derived and the direction of teacher education for this was discussed.
Development Model of Basic ECG Algorithm Interpretation based on Android Application to Increase Ability of Nurses

Introduction: ECG interpretation ability by nurses is still not appropriate, thus affecting the accuracy and speed of the next action that will be given to patients to reduce mortality. This study aimed to develop the use of an Android system based ECG interpretation algorithm application to improve the ability of nurse. Methods: Research development design to develop the Android system based ECG interpretation algorithm application. The sampling method used purposive sampling as many as 90 nurses in Universitas Airlangga Hospital, Surabaya, Indonesia. The independent variables were interpretation skills (rhythm, frequency, pacemaker, axis, extrasistole, block, enlargement of heart muscle, coronary heart disease, conclusion). The instruments that are used are ECG recording, ECG interpretation sheet, and focus group disscusion. The analysis used an independent t-test with a significance level of α ≤ 0.05. Results: The results of developing an ECG interpretation algorithm application based on the Android system have received recommendations from experts and feasibility tests have been carried out. There was a relationship between basic ECG interpretation capabilities with the use of an android system based ECG interpretation algorithm application. Increasing the ability of nurses had p value of 0,000. Conclusion: The application of an ECG interpretation algorithm based on an android system can improve nurses' abilities in interpreting basic ECG. For future researchers, it is necessary to develop and refine the Android system-based ECG interpretation algorithm application and this can be applied on a case-by-case basis.
Analysis the impact of digital campaign on healthcare provider-waste management provider

This research aims to analyze the impact of digital campaigns on the relationship between health service providers and waste management service providers using qualitative methods. This research utilizes literature studies related to the research topic. This qualitative data will be analyzed using an inductive approach to identify patterns, thematic findings, and dynamics that emerge in the relationship between health service providers and waste management service providers after the implementation of the digital campaign. The results of this study are expected to provide in-depth insights into the role of digital campaigns in shaping and improving relationships between the healthcare and waste management sectors and the implications for sustainable waste management practices.
EMOTIONAL LEXICONS IN FOOD AND DRINK ADVERTISEMENTS

The effectiveness of advertisement content is one of the most significant factors affecting consumers’ affective and behavioral intentions. Consumption emotions which consumers experience before, during and after using a product partly derive from their exposure to the advertisement. Various consumption emotions for different food products and experiences have been explored and validated. However, there has been little research that scrutinizes emotional lexicons in advertisements and how these lexicons affect consumer behaviors. This empirical research adopted content and thematic analysis to explore the emotional lexicons used in food and beverage advertisements. The study examined advertisers’ perspectives of emotional lexicon and the degree of influence on consumers’ perceptions and behaviors. The findings showed that three themes of the emotional words and expressions were used in food and beverage advertisements: sensory, affective, and behavioral evocative. This study made theoretical contributions to the knowledge of consumption emotion and provided valuable insights into the method and process of creating emotional lexicon. It also proposed a working list of emotional lexicons helpful for food and beverage advertising
IMPROVING STUDENTS’ ENGAGEMENT THROUGH THE PROGRESSION OF READING, WRITING, AND PRESENTING IN STUDYING LITERATURE

This study was conducted to examine the implementation of a pedagogical approach called the progression of reading, writing, and presenting in studying American and British Literature among English majors at the Foreign Trade University. By drawing upon the principles of studentcentered learning, this study investigated the impact of this approach on students' levels of engagement. Within the framework of Fredericks et al. (2004), this study was expected to shed light on the current state of students' behavioral, emotional, and cognitive engagement with the course through a comprehensive analysis of 38 students' responses obtained from multiple sources, including questionnaires, self-reports, and interviews. The findings revealed a comprehensive understanding of students' engagement in learning American and British Literature and suggested effective strategies for enhancing student engagement in literature courses.
TECHNIQUES AND INNOVATIONS FOR WISDOM TOOTH EXTRACTIONS

Background: Wisdom tooth extractions are common surgical procedures associated with post-operative complications. This quantitative analysis aimed to evaluate the efficacy of various surgical techniques and innovations in wisdom tooth extractions. Methods: A systematic review was conducted, searching databases for studies published between 2010 and 2024. Inclusion criteria encompassed studies investigating surgical techniques, innovations, and outcomes in wisdom tooth extractions. Data were synthesized, and meta-analyses were performed where applicable. Results: Thirty-two studies met the inclusion criteria. Minimally invasive techniques, including piezoelectric surgery and laser-assisted surgery, demonstrated significant reductions in post-operative pain scores compared to conventional techniques (mean difference: -1.5, 95% CI: -2.3 to -0.7, p < 0.001). Advanced imaging modalities, such as cone-beam computed tomography (CBCT) and computer-aided design/computer-aided manufacturing (CAD/CAM) technology, were associated with lower complication rates compared to conventional surgery (odds ratio: 0.45, 95% CI: 0.32 to 0.63, p < 0.001). Biologic adjuncts, such as platelet-rich plasma (PRP), demonstrated enhanced bone formation and reduced post-operative infection rates compared to controls (mean difference in bone formation: 2.0 mm, 95% CI: 1.5 to 2.5, p < 0.001). Conclusion: This quantitative analysis highlights the efficacy of minimally invasive techniques, advanced imaging modalities, and biologic adjuncts in improving outcomes of wisdom tooth extractions. Integration of these innovations into clinical practice has the potential to optimize patient care and enhance surgical outcomes.