Reviewerly/exHarmony huggingface dataset:
Effectiveness of Character-Based Comic Media on Environmental Conservation Sub-Material Learning Outcomes

The utilization of learning media is one of the alternatives to increase knowledge for students, especially biology learning. In addition, student character can be improved through media in which there is character insertion. Thus, an innovative learning media is needed to improve knowledge and character through character-based comics on environmental conservation submaterial. This research method is a quantitative experiment, with a pretest-posttest control group research design. The sample consisted of 28 control class students and 30 experimental class students. The instruments were 20 multiple choice questions and 22 character questionnaire statements. Data analysis techniques include knowledge assessment measured using the Independent samples t-test formula. The results of data analysis showed that the knowledge of experimental class students increased significantly, the learning outcomes in the experimental class showed a higher average of 86.67 while the control class was 74.46, the average difference in learning outcomes between experimental and control classes was evidenced by the independent samples t-test test value of 0.00 &lt;0.05, and student character showed a percentage of 81.44% in the excellent category. It is concluded that character-based comic media on environmental conservation submaterial can help improve cognitive learning outcomes and student character.
The Leitmotif Structure of ‘Signs and Recognition’: Music of &lt;Signs&gt;

the God's message.
AN ANALYSIS OF EXPRESSIVE SPEECH ACTS IN ONLINE DISCUSSION THROUGH WHATSAPP GROUP

This study aimed to investigate an analysis of students’ expressive speech acts in online discussion through Whatssapp group. The method used was descriptive qualitative research, and the data source contained expressive speech acts between teacher and students in online teaching and learning. The data came from online teaching and learning interactions between teachers and students for Indonesian language in class VIII at SMP Negeri 35 Makassar with total of 246 students consisted of nine classes and a total of 56 students as respondents. The results found that expressive speech acts can be found everywhere, including in learning Indonesia subject through apologizing, tempting, motivating, hoping, praising, gratitude, thanking, congratulation, criticizing forms and functions of teacher and students’ expressive speech acts. It can be concluded that many expressive speech acts are used in the interactions between teachers and students in online discussion. This research can contribute to the interaction between students and teacher regarding the expressive speech acts in online teaching and learning interactions through WhatssApp group discussion.
Organizational commitment as mediating between administrative creativity and job performance among department managers at Al Hussein bin Talal University

This study examines the impact of organizational commitment on administrative creativity and job performance among department managers at Al Hussein bin Talal University. Job performance refers to managers' ability to accomplish their job-related duties efficiently and effectively. Administrative creativity refers to managers' ability to generate innovative ideas and solutions. Organizational commitment is loyalty to an organization. Quantitative research will be used in the study. Surveys will be distributed to department managers at Al Hussein bin Talal University to collect data. The study will use validated measures of administrative creativity, organizational commitment, and job performance. To examine the relationships and mediating effects among the variables, statistical analyses will be performed, such as correlation analysis and mediation analysis. This study will impact human resource management and organizational development practices at Al Hussein bin Talal University. The university can improve department manager performance by fostering a culture that encourages innovation and administrative creativity. In addition, understanding organizational commitment can improve employee commitment to the organization.
Machine Learning for Anomaly Detection in Accounting Records: A Comprehensive Study

Maintaining the integrity of accounting records is vital for financial transparency, regulatory compliance, and fraud prevention. This study explores the application of Machine Learning (ML) techniques for anomaly detection in accounting records, shedding light on the evolving landscape of financial data analysis. It emphasizes the critical role of accurate accounting records in business operations, financial reporting, and regulatory adherence. Amidst increasing transaction complexity, traditional audit methods face challenges in detecting unnoticed irregularities. A detailed examination of ML methodologies, including clustering, classification, and neural networks, showcases their potential in identifying anomalies within accounting data. The study discusses data preprocessing, feature engineering, model selection, and evaluation criteria essential for robust anomaly detection. Real-world case studies illustrate how ML-driven anomaly detection enhances traditional accounting practices, improving accuracy and efficiency. It underscores ML's proactive role in preventing fraud, errors, and compliance breaches. Ethical and regulatory considerations in ML implementation are addressed, highlighting the importance of transparency, accountability, and responsible AI practices. This study serves as a valuable resource for accounting professionals and regulatory authorities, emphasizing ML's transformative impact on maintaining financial accuracy and regulatory compliance.
How Search Engine Optimization (SEO) Grew from Nascent Stages to AI

The journey of search engine optimization (SEO) from its nascent stage to the present day has been remarkable. Emerging alongside the proliferation of search engines, SEO quickly became an indispensable tool for businesses and marketers striving to enhance their online visibility, attract traffic, and improve rankings. However, as search algorithms advanced, SEO professionals encountered a dynamic landscape marked by evolving trends and new obstacles. For this reason, over time, the factors influencing website ranking have undergone a significant expansion, evolving from a limited set to a multifaceted array. Specific components, such as high-quality backlinks, mobile optimization, local SEO strategies, integration with social media platforms, and the optimization of user experience, have emerged as pivotal determinants of SEO success. These elements assume a critical role in achieving elevated rankings and heightened visibility across search engines, thereby shaping the contemporary landscape of SEO practices. More recently, as search engines and SEO evolve in sophistication, Artificial Intelligence (AI) has found relevance in its integration into SEO. This involvement of AI amidst its benefits, also introduced new challenges and ethical dilemmas into the discuss on search engine optimization (SEO). SEO strategies must exhibit adaptability to maintain efficacy in driving visibility, traffic, and revenue. It is crucial to strike a balance between data-driven decision-making and empathetic marketing. Businesses shouldn't rely solely on AI to preserve the human touch in their marketing endeavors. Hence, navigating the ever-changing terrain of SEO requires marketers and SEO experts to remain attuned to emerging trends and adept at adapting strategies to meet evolving challenges. By leveraging the diverse array of factors influencing SEO success, businesses can enhance their online presence and effectively engage with their target audience in the competitive digital landscape. For this reason, ethical considerations, including data privacy and customer trust, mustn't be side-lined in favor of optimization. Prioritizing ethical practices over all else safeguards the integrity of SEO efforts amidst AI integration.
Enhancing Fraud Detection in Financial Statements with Deep Learning: An Audit Perspective

Financial fraud persists as a formidable challenge, necessitating continuous audit innovations to uphold financial statement integrity. This study explores the application of Deep Learning (DL) techniques in bolstering fraud detection within financial audits. It emphasizes the pivotal role of audits in preserving trust and transparency in business. Highlighting the evolving nature of financial fraud, the study underscores the need for auditors to adapt to sophisticated schemes. An examination of DL methodologies reveals the potential of neural networks, anomaly detection, and predictive modeling in uncovering hidden fraudulent activities. The discourse encompasses data-driven strategies, model architectures, and tailored feature engineering. Real-world case studies demonstrate how DL-driven fraud detection enhances traditional methods by improving accuracy and reducing false positives. The study stresses the importance of continuous monitoring, proactive risk mitigation, and timely fraud prevention. Additionally, it addresses ethical and regulatory considerations, advocating for transparency and responsible AI practices in auditing. In conclusion, this study serves as a valuable resource for auditors and regulators, highlighting the transformative impact of DL in fortifying fraud detection and preserving financial reporting integrity.
An Indian Society on Hate Talk: the Differences and Lack of Discourse

In India, a society and polity with a mix of cultures, ethnicities, languages, religions, castes and other identities in the country, it is crucial we understand the distinction between free speech and hate speech
AI Integration for Three Language Formula: Advancing Viksit Bharat 2047 Mission

The National Education Policy (NEP) 2020 emphasizes the Three Language Formula to promote multilingualism and national integration in India. This paper explores the integration of Artificial Intelligence (AI) technologies to effectively implement the Three Language Formula. It discusses the significance of multilingual education, challenges, and proposes AI-driven solutions. Furthermore, it examines how this initiative aligns with the ViksitBharat 2047 mission, envisioning the role of AI in fostering a developed India by 2047. Through case studies and analysis, the paper provides insights into leveraging AI to realize the goals of NEP 2020, contributing to education advancement and national development. This research is crucial for policymakers, educators, and stakeholders aiming to shape India's educational future.
A Probe into the Sense of Efficacy of the Teachers

The concept of teachers’ Sense of Efficacy refers to person’s own belief in his or her capacity to perform their behaviors necessary to produce specific performance attainments in the institution. To ascertain the present status of teachers’ Sense of Efficacy of the school teachers of West Bengal, the present study was carried out through the Descriptive Survey Method by administering Teachers’ Sense of Efficacy Scale (TSES) (Tschannen-Moran &amp; Woolfolk Hoy, 2001) on a random sample of 616 school teachers of West Bengal. The results of the study reflected that on an average the teachers of West Bengal were highly scored in all the subscales of Sense of Efficacy and also in Sense of Efficacy (in Totality). It might be concluded that, the teachers may be perform well in their academic activities and teach efficiently to the students that emphasis the good productivity of quality education.
Perceived Health Behaviors and Learning Needs of Patients with Myocardial Infarction

Introduction: - Myocardial infarction is one of the foremost cardiovascular disease causes of mortality and morbidity worldwide. The prevention of this disease requires continuous monitoring and rehabilitative management. It can be achieved by the health promotion of patients using effective, planned educational programs and lifestyle modification by the patient. Patients perceived that their learning needs were unmet and that the information provided was too general. Hence, assessing the healthy heart habits performed by the patient and the patient’s preference regarding learning needs is crucial. The descriptive study is intended to identify the perceived health behaviors and learning needs of patients with myocardial infarction for the first time. Methodology: A quantitative descriptive design was used in this present study. The study included 102 newly diagnosed patients with MI carefully chosen by the non-probability convenience selection method. Information was collected using a patient profile (socio-demographic data, clinical data, and clinical parameters), a Modified cardiac health behavior scale (MCHBS), and a Cardiac patient's learning needs inventory (CPLNI). Results: -The present study result showed that subjects with MI for the first time had a high level of perceived learning needs of 164.11 + 22.28, with symptoms management was 27.61 + 3.763, medication information was 23.15 + 3.010, diet information was 23.12 + 3.148 were the areas perceived as high learning need information among the subjects. Only 11 (10.8%) subjects had a high perception of cardiac health behavior, among which were controlling risk habits and was 14.53 + 3.16. Medication adherence was only 6.76 + 1.89, perception of the subjects regarding dietary management was 19.47 + 4.15, and blood pressure control was 5.09 + 2.13 as considered essential in maintaining a healthy heart. Interestingly, the findings show that subjects with the perception of higher learning needs showed a negatively weak correlation with a lesser perception of health behavior, which is not a statistically significant level at p &gt;0.05. The study highlighted that exercise, habits, and RBS had a statistically significant association with perceived health behavior (χ2= 18.52, p &lt;0.001), (χ2=20.133, p =0.013), (χ2=9.067, p=0.037) respectively. Also, the exposure of subjects to mass media (χ2 =15.01, p&lt;0.05), diversional activities practiced (χ2 =19.08, p &lt;0.01), perception about the prognosis (χ2=7.22, p&lt;0.02), habits (χ2= 13.68, p&lt;0.03) level had a statistically significant association with the perceived learning needs. Conclusion: - Patients’ health behaviors practices and learning needs will change according to their perceptions. Determining the learning needs will help to guide the patient to achieve good cardiac health behaviors practice, subsequently reducing the reoccurrence of myocardial infarction.
Perception of M.ed. Student-teachers Towards Internship as a Part of Teacher Training Programme

Teaching is an exciting and rewarding activity but like other professions it is demanding as it requires that its practitioners clearly understand what should be done to bring about the most desirable learning in the pupil and be highly proficient in the skills necessary to carry out these tasks. All the teachers training institutions are not only imparting theoretical but also practical knowledge and skill in teaching different subjects to prospective teachers. There are many parts of teacher training programme like Internship, sessional Work, Project work, micro and macro teaching etc. Internship is an integral part of professional preparation that includes practice – teaching and wide variety of field experience under the guidance of a competent or expert supervisor. Internship in M.Ed. is very essential for today’s teacher because it gives proper training to the student-teachers for better understanding of all the students. It builds confidence among the student-teachers. Therefore, the objective of the study is to know the perception of M.Ed. students-teachers towards the internship programme. In the present study, the researcher has used the descriptive method of research. The total sample includes 100 M.Ed. students-teachers from three M.Ed. colleges of Jammu. A Self-constructed questionnaire was prepared to collect the required data. After collecting the data, the frequencies were calculated to analyze the data. The findings of the study revealed positive perception of student-teachers towards internship as a part of professional preparation of teacher. The present study is helpful for educationists, practitioners, students, stakeholders, policy-makers, teachers and parents.
A Study on Growing Popularity of Digital Wallets among Youngsters in Kerala

Any economy's lifeblood is seen as being money. Transactions are now simple in the current environment because to the constant advancement of technology, the internet, and mobile phones. Money transfers and other payment methods are offered on the market. The primary component of digitization is mobile wallets. As opposed to using cash, people prefer to make digital payments. People now prefer cashless transactions more than they did in the past due to demonetization and the unanticipated COVID outbreak. Because money notes are handled by many different people, the transmission of pathogens is also possible. Mobile wallets have greatly simplified and improved our way of living. A digital wallet safely and conveniently maintains all of the users' payment information. There is far less need to carry actual wallets as a result. Only the mobile wallet allows a smart phone to be used as a wallet. These wallets allow for the secure addition of money as well as direct bank account integration. India is moving towards a digital future. Digital wallets are a key component of the digitization process. Within this little time frame. Based on diverse observations, several academics from across the world have investigated digital wallets. However, there is no evidence that anyone has looked into how prevalent digital wallets are among young people. Therefore, the goal of the study is to determine how common digital wallets are among young people. In this study, the gender disparity in usage, transaction volume, usage experience, and transaction count in digital wallets is being examined.
Deblurring using Reverse Filtering Techniques: An Experimental Analysis

Images are an integral part of life. Blurring an image is a process that makes the image less sharp and distorts the detail of an image. The images got blurred due to atmospheric noise, improper camera setting, and relative motion between the camera and the scene. Deblurring is the process of recovering the sharp image from the blurred image. The types of blurs include Average blur, Motion blur, Defocus blur, Gaussian blur, etc. Mainly deblurring techniques are categorised into blind image deconvolution and nonblind image deconvolution. There exist many deblurring techniques in the literature. Deblurring using reverse filtering is to suppress the effect of the filter using the filter itself as many times as needed but without knowing its internal structure. The filter is regarded as a black box. This paper presents the experimental analysis of existing reverse filtering techniques such as zero order reverse filtering (T-method), Rendition method (R-method), P-method, and TDA (Total Derivative Approximation). The methods considered in the paper are spatial domain methods.
Enhancing Teacher Education: Cultivating the Architects of Tomorrow’s Mind

This article underscores the urgent need for a revamp in teacher education programs to better equip educators as architects of future minds. In the face of rapid technological advancements and evolving educational paradigms, educators' roles have become increasingly intricate. The article explores current challenges in teacher education and advocates for trans-formative approaches aligned with the dynamic needs of 21st-century learners. Key themes include integrating technology, fostering critical thinking, and promoting culturally responsive pedagogy. Drawing on research and best practices, the article proposes a comprehensive framework emphasizing experiential learning, interdisciplinary approaches, and continuous professional development. It emphasizes collaboration between academia, institutions, and policymakers to create a supportive ecosystem. The article advocates for innovative teaching methodologies like project-based learning to prepare educators for the evolving educational landscape. By reviewing existing teacher education models, the article aims to offer insights into effective strategies, emphasizing the significance of fostering a growth mindset among educators. Ultimately, it calls for a paradigm shift, positioning educators as architects of tomorrow's minds, ready to shape an empowered generation capable of meeting future challenges.
Cybersecurity in Tanzania: Opportunities and Challenges

Tanzania, like many developing nations, is undergoing rapid digitalization. While this brings numerous benefits, it also opens the door to increased cybersecurity threats. This abstract explores the unique landscape of cybersecurity in Tanzania, highlighting both the opportunities in emerging digital technology, government initiatives, increased awareness and collaborative approach. On the other hand it describe the challenges that lie ahead such as cybercrime landscape, limited digital literacy, data privacy concerns, inadequate resources and infrastructures.
Accelerating the process of text data corpora generation by the deterministic method

The object of research is the process of generating text data corpora using the CorDeGen method. The problem solved in this study is the insufficient efficiency of generating corpora of text data by the CorDeGen method according to the speed criterion. Based on the analysis of the abstract CorDeGen method – the steps it consists of, the algorithm that implements it – the possibilities of its parallelization have been determined. As a result, two new modified methods of the base CorDeGen method were developed: “naive” parallel and parallel. These methods differ from each other in whether they preserve the order of terms in the generated texts compared to the texts generated by the base method (“naive” parallel does not preserve, parallel does). Using the .NET platform and the C# programming language, the software implementation of both proposed methods was performed in this work; a property-based testing methodology was used to validate both implementations. The results of efficiency testing showed that for corpora of sufficiently large sizes, the use of parallel CorDeGen methods speeds up the generation time by 2 times, compared to the base method. The acceleration effect is explained precisely by the parallelization of the process of generating the next term – its creation, calculation of the number of occurrences of texts, and recording – which takes most of the time in the base method. This means that if it is necessary to generate sufficiently large corpora in a limited time, in practice it is reasonable to use the developed parallel methods of CorDeGen instead of the base one. The choice of a particular parallel method (naive or conventional) for a practical application depends on whether or not the ability to predict the order of terms in the generated texts is important