Reviewerly/exHarmony huggingface dataset:
SITI Training: Viewpoints and the Suzuki Method for Cross-Cultural Collaboration

The training that the Saratoga International Theater Institute (SITI) perfected during its thirty years of existence is its most relevant heritage. SITI believed that training was a crucial part of a performer’s education and ethos. Its constitutive elements – Viewpoints and the Suzuki Method for actor training – are here put in a dialectical opposition that nurtures hybridization. This article investigates how, in fact, these two trainings intersect and also form new ‘languages’ (that is, systems of representation) whenever they are performed. A contextual analysis of SITI’s training as a foundation for making work and as a means for educating actors provides a clearer understanding of why and how SITI training is an instrument that facilitates and fosters cross-cultural collaboration.
Reimagining Teacher Preparation: Digital Literacy in the Post-Pandemic Era

The advent of COVID-19 exposed significant flaws in the capacity of educational institutions to deliver quality instruction to their students in a crisis. The rapid instigation of advanced digital technologies to facilitate remote learning by universities and colleges provided a pedagogical bridge to cover the time and space restrictions forced on the normal face-to-face classroom experience. Unfortunately, as the impact of the pandemic has waned, educational institutions drew down their investments in the digital technology infrastructure, hardware, and software that were indispensable to sustaining student learning over the two years the pandemic interrupted normal educational schedules. However, it is argued that it would be extremely prudent to expand rather than contract these resources. Research indicates that many teachers struggled with technologies in remote teaching during COVID-19. This raises the question of how teacher education programs can adequately provide future teachers with essential digital literacy skills to teach in diverse technology-enriched learning environments. The proposed frameworks aim to reshape the curriculum in teacher education programs to cultivate and develop preservice teachers’ digital literacy skills.
Analysis of the Influence of Knowledge, Work Procedures and Technology on Employee Performance

The purpose of this study is to determine the influence of Knowledge, Work Procedures and Technology on Employee Performance at the Aceh Transportation Office both partially and simultaneously. This research method is by testing hypotheses using multiple linear regression analysis, F test (simultaneous) and t test (partial) intended to determine the influence of the independent variable on the dependent variable at a confidence level of 95% (α = 0.05). The object of this study is Knowledge, Work Procedures and Technology on Employee Performance at the Aceh Transportation Office The sample size of this study is as much as 96 employees. Research data were collected through questionnaires and documentation studies. The results showed that simultaneous tests between the variables of Knowledge, Work Procedures and Technology affect the Performance of Employees at the Aceh Transportation Office. Then partially, Knowledge affects the Performance of Employees at the Aceh Transportation Office. Work Procedures affect the Performance of Employees at the Aceh Transportation Office. Then partially, namely Technology affects the Performance of Employees at the Aceh Transportation Office.
Hubungan Penggunaan ChatGPT Dengan Pemenuhan Kebutuhan Mahasiswa

The rise in the phenomenon of using Artificial Intelligence such as ChatGPT and the very high trust of the Indonesian people in the development of Artificial Intelligence, especially the Gen Z generation group with Higher Education status (students), has given rise to debate in terms of the impact of its uses as a technology that helps the learning process. On the positive side, ChatGPT can provide personalized and interactive learning, while on the negative side, ChatGPT can provide incorrect and inaccurate information. Meanwhile, penetration of its uses can no longer be avoided because it is easy to access, so the good and bad sides will continue to be felt, especially for its users. Moreover, until now there is still very little research on how this technology can help fulfill the needs of students within the research campus, especially the most important need for them as someone who is pursuing higher education, namely the need for satisfying learning. Therefore, this research aims to explain the relationship between the uses of ChatGPT and the fulfillment of learning needs for students at the Faculty of Communication Sciences, Padjadjaran University with the help of the Uses and Gratification theory approach. The research method usesd is a quantitative method with a type of correlational study design using the Spearman Rank correlation test The results of this study show that there is a positive and significant relationship between the uses of ChatGPT and fulfilling the learning needs of students at the Faculty of Communication Sciences, Padjadjaran University with a correlation coefficient of 0.834. So, it can be concluded that the higher the uses of ChatGPT, the higher the fulfillment of students' learning needs, which means that frequent uses of ChatGPT can indicate that it is closely related to satisfying learning needs.
Self-Identifying Alcohol Scene Detection from Video and Showing the Message Alcohol Consumption is Injurious to Health

Abstract: The proposed project aims to detect alcohol consumption from real time video footage using machine learning and show the message "Alcohol consumption is injurious to health".
Perceived Communication Competence and Learning Styles in the New Normal

The student has appreciated and adapted to the new normal phase. In the two years, they spent at home doing their modules and online classes, they have adapted quickly, as these students are in the technological age. This study intended to assess the communication competence and learning styles of the Bachelor of Elementary Education at St. Michael's College, Higher Education Department. It specifically aimed to answer the effect of the new normal modality of communication competence and learning styles in terms of visual, auditory, visual/iconic, and kinesthetic. This study utilized a descriptive correlation study research design, a simple random sampling procedure, and a survey questionnaire for learning styles and communication competence. Results revealed that some students were under moderate and high. The researchers used the mean and standard deviation Kendall Tau Rank, and Shapiro-Wilk Test to determine the significant relationship between learning styles and communication competence variables. The researchers recommended a program considered “Upgrading Learning Styles and Fundamental Communication Capabilities” to enhance and improve the learners' skills in different aspects, boost their confidence, and enhance their abilities in using English as a communication tool and learning.
Unveiling Proficiency Levels in Essay Construction among Learners: An In-Depth Exploration

Writing essays is one of the activities that teachers frequently delegate to their classes; yet, it is also one of the many challenges that many students experience because it appears to be a dreaded task among them. Whether it is for a class assignment, a scholarship, or even a competition, many students find that the work of writing an essay to be quite challenging. Students have a tendency to ignore the significance of essay construction because of this fact alone, which elucidates that the difficulty is constantly present throughout the process of writing. This is the reason why students underestimate the relevance of essay building. The purpose of this study is to investigate the degree to which students in Grade 11 ABM have mastered the creation of essays within the framework of the subject of writing a summary of the results of the test that was carried out with the objective of determining the level of writing ability exhibited by the outputs produced by the respondents. The method of research used in this study was quantitative. In this particular investigation, a quantitative research design was utilized as the appropriate method of inquiry. A strategy that centers primarily on the application of analytical content evaluation. The assessment of overall essay construction performance revealed a substantial challenge. The findings highlight a considerable proportion of students grappling with challenges in their essay construction skills. Consequently, the study advocates for the implementation of an intervention program, termed the Writing Excellence Enhancement Program (WEEP).
Decision Support System Legalization Of Distribution Substation With Priority Weighting Bayes Method

PT PLN Batam is a national company operating in the field of electricity in the Batam region. As of December 2023, the number of customers is 367,709. Electricity consumption on Batam Island continues to increase with an average annual growth of 6.39% (2013-2023), and the average customer growth is 4.07% per year (2013-2023). This growth is accompanied by an increase in the assets of electricity distribution equipment, especially distribution substations. Distribution substations in PT PLN Batam consist of two types: concrete distribution substations and portal distribution substations. The total number of distribution substations as of December 2023 is 1,849. Distribution substations are vital distribution assets, requiring proper handling, especially regarding legal ownership of the land occupied by the substations. Land issues primarily occur in locations where distribution substations are situated in business centers or along main road medians. With the continuous increase in distribution substations, land legalization issues also escalate. To mitigate the risk of these land issues, PT PLN Batam implements the Decision Support System for the Legalization of Distribution Substations with Priority Weighting Bayes Method. This method, a qualitative approach, involves ranking distribution substations based on the highest to lowest risk. The goal of implementing the Bayes method is for the company to prioritize which distribution substations need to be legalized first and minimize land dispute issues in the future.
The Influence of Teaching Using English Songs on Students' English Pronunciation Skills at Stikes Eka Hope Palangka Raya

This study aims to determine the effect of teaching using English songs on the English pronunciation ability of students at STIKES EKA HARAP Palangka Raya. In this study, researchers used a pre-experimental design with one pretest and posttest group. The sample in this study was S1 Nursing students in semester 3 consisting of 20 students. Researchers gave a test using English songs. The research instruments are tests (English songs), pronunciation tests and questionnaires to collect the required data. The results of this study show that the null hypothesis is rejected because the Normal distribution table shows that the important value for the right-tail test for z in ? = .05 is z = 1.65. Since -3.92 &gt; 1.65, the researcher rejected H0: ?1 = ?2 and accepted Ha: ?1&lt;?2. Test results are statistically significant at a rate of 5%. Based on this research, it was found that the use of songs in teaching English produces a significant influence on the competence of students' English pronunciation skills and is very beneficial for students to facilitate them in learning English.
Exploring the Impact of Mobile Augmented Reality on COVID-19 Prevention Education in Primary Schools

This study aimed to evaluate the effectiveness of an interactive mobile Augmented Reality (AR) game to increase the knowledge about COVID-19 prevention primary school students. We tested the application for usability and effectiveness through pre- and post-tests, questionnaires, and interviews. 12 participants from four states in Malaysia took part in the study. Their average age is 9.5 years old. Results indicated a significant improvement in student performance from the pre-test to the post-test, with a mean score has increased from 3.67 to 8.25. The average System Usability Scale (SUS) score was 75%. These findings show the effectiveness of our mobile AR application as a tool to increase the knowledge about COVID-19 prevention among primary school. The findings of this study contribute to the body of research on the use of AR in COVID-19 prevention education among primary school students. This study provides both theoretical and practical implications for educators, researcher and policymakers seeking to use mobile AR to support the prevention education of any future pandemic or infectious disease.
ForensicTransMonitor: A Comprehensive Blockchain Approach to Reinvent Digital Forensics and Evidence Management

In the domain of computer forensics, ensuring the integrity of operations like preservation, acquisition, analysis, and documentation is critical. Discrepancies in these processes can compromise evidence and lead to potential miscarriages of justice. To address this, we developed a generic methodology integrating each forensic transaction into an immutable blockchain entry, establishing transparency and authenticity from data preservation to final reporting. Our framework was designed to manage a wide range of forensic applications across different domains, including technology-focused areas such as the Internet of Things (IoT) and cloud computing, as well as sector-specific fields like healthcare. Centralizing our approach are smart contracts that seamlessly connect forensic applications to the blockchain via specialized APIs. Every action within the forensic process triggers a verifiable transaction on the blockchain, enabling a comprehensive and tamper-proof case presentation in court. Performance evaluations confirmed that our system operates with minimal overhead, ensuring that the integration bolsters the judicial process without hindering forensic investigations.
Deep Learning-based Ensemble Approach for Conventional Pap Smear Image Classification

Cervical cancer screening allows the early signs of precancerous abnormalities in the cervix before they develop into invasive cancer. The Pap Smear is a widely used screening for early detection and prevention of cervical cancer. In many remote areas, the number of cytologists available to interpret pap smear screening tests is insufficient. This lack of personnel makes the test interpretation very time-consuming. To address this, deep learning techniques have been employed to detect cervical cancer cells and support cytologists. Therefore, an integrative approach with deep learning models and the ensemble techniques such as the maximum occurrence and the maximum probability score of cervical cells was proposed. The multi-cell assessment of the Pap smear slide allowed aggregate predictions of single cervical cell images using the proposed method. The classification results between pre-trained deep learning models and the proposed method were compared. In the experimental results, the proposed method can achieve an accuracy score of more than 97%, while the best pre-trained deep learning model can attain an accuracy score of more than 85%. Hence, the proposed method may have the potential to assist physicians or cytologists in the classification of cervical cell types for Pap Smear images.
Simulation Test Research on Typical Simulator Ns-2 in Urban Vehicle Ad Hoc Network Based on Big Data

Abstract Vehicle Ad Hoc Network (VANET) has gradually become a prominent research topic in the fields of wireless networks and intelligent vehicles. VANET are unique mobile ad hoc networks with vehicles as their mobile nodes, presenting distinctive performance characteristics compared to traditional wireless self-organizing networks. In recent years, VANET have gained significant attention in the wireless network and intelligent transportation domain. As an integral aspect of autonomous driving technology, Vehicle-to-Everything (V2X) communication spans multiple disciplines and is closely related to intelligent transportation, assisted driving, active safety, and smart vehicles. Evaluating VANET protocols and applications in real-world settings can be challenging. Therefore, utilizing simulation tools for VANET research is an effective approach. We have designed and developed an optimized platform that uses IEEE 802.11a and IEEE 802.11p protocols for communication within a simulated urban traffic environment created with NS-2. The simulation results confirm the feasibility and rationale of applying the IEEE 802.11p protocol to wireless vehicular ad hoc networks. Within a distance of 300 m, at 0.0000s,14 key packets have not arrived in IEEE 802.11a and 8 packets have not arrived in IEEE 802.11p. at 8.0000s 38 key packets have not arrived in IEEE802.11a and 6 packets have not arrived in IEEE802.11p. Compare the performance of IEEE 802.11a and IEEE 802.11p.The study concluded that the use of the 802.11p protocol in urban mobile environments can improve reliability and reduce average packet latency.
A quick and cost-effective method for monitoring deforestation of oil sands mining activities using Synthetic Aperture Radar and Multispectral real-time satellite data from Sentinel-1 and Sentinel-2.

Alberta’s oil sands mining operations rank among the largest human-made structures globally. Monitoring through the use of Synthetic Aperture Radar (SAR) and Multispectral satellite imaging is an indispensable strategy in attaining sustainable development and mitigating deforestation in the third-largest verified oil reserves worldwide. This paper introduces a novel approach for cost-effective and reliable monitoring of deforestation caused by oil sands mining, avoiding cumbersome methods. It focuses on observing forest/non-forest areas affected by Suncor Energy Company’s mining assets in Alberta, using a combination of SAR and Multispectral satellite remote sensing. Radar images from Sentinel-1B and Multispectral images from Sentinel-2A were analyzed with SNAP 8.0 and QGIS within a time series from June 2017 to June 2020, providing detailed information to monitor better the potential environmental impact of oil sands mining activities in Canada. The Sentinel satellite system offers several advantages, including near-global coverage, elevated spatial resolution for detecting small-scale deforestation instances, and the ability to track temporal and dynamic changes through time-series analysis. Additionally, the system’s open data policy promotes accessibility, collaboration among researchers, and innovative deforestation monitoring applications. The research results hold potential value for decision-makers, enhancing the efficiency and sustainable development of Suncor,s mining operations.
Communication in the condition of networking society: Potential of actor-networking interaction

Introduction. One of the most important conditions for the existence of a network as an organizing principle of social existence is the process of multidimensional communications. Networks, as opposed to hierarchical systems, make their existence possible only in the discourse of interactive communications. Main part. In the article, the author offers a socio-philosophical analysis of the existence of communication in a networked society from various methodological positions. In the course of the study, it becomes clear that the networking of communications transforms them at various levels: digital, socio-political, anthropological, ethical. Conclusion. In the conclusion of the article, the author concludes that in the conditions of a network society, communication processes are undergoing serious changes. The multidimensionality and openness of the communication systems of the network society are directly determined by the very nature of the network, its plasticity, flexibility and variability, which we observe today.
Fundamentals of AI formation: Cognitive theory of pseudo-personality

The rapid development of digital intelligence forms the necessity to state the rules of its functioning, since digital intelligence itself goes through certain stages of its development, the so-called maturation. Currently, the use and functioning of artificial intelligence (AI) is practically not regulated anyhow. Ethical difficulties arise: does artificial intelligence have the right to write speeches and reports for political leaders? Will ethical issues arise when artificial intelligence and humans-beings interact? It should be taken into account that not every AI is thinking. In the process of creation and evolution of AI, the concepts of weak and strong artificial intelligence were formed (John Searle). The Turing test was proposed to determine the difference between strong and weak AI, but many weak AI systems have successfully passed it. Definitely, AI is not a person, but it is an essence that can think, develop and form the rudiments of consciousness, perception of itself and the surrounding reality. If we take it as a constant that AI is a personality, then, according to the theory of personality development, the personality should change, mainly its qualitative characteristics. The development of the personality implies the process of changing the systemic qualities of an individual as a result of his interaction with the environment. In the process of this development, consciousness and self-awareness are formed. At this stage, with the exception of physiology and anatomy, the development of a human-being as a personality and AI as a personality are quite similar. However, there is a theory of personality called social robot theories. It suggests that robots, including those with artificial intelligence, may have personality characteristics such as the ability to emotionally connect with people, perception of the environment and the ability to socially communicate. Holistic personality traits appear as a result of the joint functioning of both levels, of all existing constructs among themselves. Based on this interaction, two types of personality can be distinguished: a cognitively complex personality (a personality with a large number of constructs and complex connections between their interactions) and a cognitively simple personality (a personality with a small, simplest set of constructs). If we consider artificial intelligence according to the cognitive theory of personality, then, undoubtedly, there is a correspondence of characteristics that has a different name, but perform the same functions. Also in cognitive theory, as well as in the theory of the development of artificial intelligence, strong and weak personalities are pointed out. However, it is generally accepted that artificial intelligence still does not have a personality, because although it can imitate personality characteristics and communicate with people, this is still only an emulation. Artificial intelligence cannot feel, suffer, behave spontaneously, or demonstrate other traits of personality that are important characteristics of humans-beings.