Reviewerly/exHarmony huggingface dataset:
स्नातकोत्तर तहको नेपाली विषयको पाठ्यक्रममा लैङ्गिक चेतना {Gender Awareness in Postgraduate Level Nepali Curriculum}

प्रस्तुत अनुसन्धानमूलक लेख स्नातकोत्तर तह मानविकी सङ्कायको नेपाली विषयको पाठ्यक्रममा रहेका रचनामा लैङ्गिक चेतनाको विश्लेषणमा केन्द्रित छ । बदिलँदो सामाजिक मूल्यमान्यता अनुसार पाठ्यक्रममा लैङ्गिक संवेदना र त्यसको चेतनाको पाटो महत्त्वपूर्ण रहेको छ । प्रस्तुत अध्ययनमा स्नातकोत्तर तहको नेपाली विषयमा चयन गरिएका रचनामा रहेको लैङ्गिक चेतनाको अवस्थालाई लैङ्गिकताको सैद्धान्तिक मान्यताका आधारमा विश्लेषण गरिएको छ । यस अध्ययनमा आधुनिक नेपाली साहित्यका आख्यान, नाटक र कविताकाव्यका पाठ्यक्रममा समाविष्ट रचनाहरूको लैङ्गिक प्रतिनिधित्व र लैङ्गिक प्रतिरोधी चेतनाका पक्षबाट अध्ययन गर्दा पाठ्यसामग्रीको गहन पठनबाट प्राप्त सामग्रीलाई विश्लेषणात्मक विधिको उपयोग गरिएको छ । स्नातकोत्तर तह नेपाली विषयको पाठ्यक्रमको विश्लेषणका क्रममा यसमा लैङ्गिक प्रतिनिधित्व र समताको अवस्था, महिला र पुरुषले निर्वाह गर्ने परम्परागत भूमिका, लैङ्गिक उत्पीडनका विरुद्धको प्रतिरोध तथा सामाजिक न्यायका दृष्टिले पाठ्यक्रममा रहेका पाठहरूको लैङ्गिक विश्लेषण गरिएको छ । पाठहरूको विश्लेषणको आधारलाई व्यवस्थित गर्न पाठको तालिकीकरण गरी उक्त तालिकाका आधारमा पाठ्यक्रमका विधाहरूको पाठपरक र विषयवस्तुपरक विश्लेषण गरिएको छ । यस आधारमा स्नातकोत्तर तहको नेपाली पाठ्यक्रममा प्रतिनिधित्व, सन्तुलन र समन्वयका दृष्टिले बढी मात्रामा पुरुषपक्षीय भएको निष्कर्ष प्रस्तुत गरिएको छ । गुणात्मक ढाँचा अवलम्बन गरिएको यस अनुसन्धानमा लैङ्गिक संवेदना र पाठ्यक्रम तथा पाठ्यक्रममा रहेका पाठमा लैङ्गिक सन्तुलनको पक्ष समावेशी हुन नसकेको निष्कर्ष समेत प्रस्तुत अध्ययनबाट प्राप्त भएको छ । {This research article focuses on the analysis of gender awareness in the composition of the postgraduate level curriculum of Nepali subject in the Faculty of Humanities and Social Sciences. According to changing social values, gender sensitivity and its awareness are important in the curriculum. In this study, the status of gender consciousness in the selected works on Nepali subjects at the post-graduate level has been analyzed based on the theoretical recognition of gender. In this study, the gender representation of works within the curriculum of modern Nepali literature, including narratives, dramas, and poetry, along with gender resistance consciousness, has been examined. The material obtained from the intensive reading of textbooks was analyzed using the analytical method. During the analysis of the postgraduate-level Nepali subject curriculum, this study examined gender representation, the state of equality, traditional roles performed by women and men, resistance against gender oppression, and social justice. To organize the foundation of the textual analysis, genres of the courses were subjected to both textual and thematic analyses, using tabulation as a tool. Consequently, the conclusion was drawn that postgraduate Nepali courses exhibit a bias towards male representation, lacking balance and coordination. Within the qualitative framework of this research, it was also found that gender sensitivity and the aspect of gender balance were not incorporated into the curriculum.}
GestureFlow: Intutive Multimedia Interactor

Gesture Flow: Intutive Multimedia Control is a project aimed at revolutionizing the way users interact with digital media. Leveraging cutting-edge technologies and innovative design principles, this project introduces a media player that incorporates intuitive interactions and augments the user's senses. By merging the physical and digital realms, the Intutive Multimedia Interactor Media Player provides an immersive and seamless media experience. The key objective of this project is to enhance user engagement and convenience while consuming digital media content. The Intutive Multimedia Interactor Media Player utilizes advanced gesture recognition through image processing techniques to enable users to control media playback and access content effortlessly. Users can, pause, play, forward, rewind, adjust volume, and perform other playback functions using specific hand gestures.
INTEGRATION OF ARTIFICIAL INTELLIGENCE INTO THE BLOCKCHAIN AND CRYPTOCURRENCY MARKET

This article explores the transformative potential of integrating artificial intelligence (AI) into blockchain technology and the cryptocurrency market. Highlighting the growing attention towards blockchain and cryptocurrencies, emphasizing their decentralized, secure, and transparent nature. However, challenges, including the need to address scalability issues and ensure responsible usage, prompt a focus on AI integration as a viable solution. The study delves into the benefits of AI in the cryptocurrency market, showcasing its ability to predict trends, identify risks, and optimize trading strategies. The research emphasizes the relevance of investigating the integration of AI into blockchain and its specific applications, particularly in detecting and preventing fraud. The article recognizes the potential for increased efficiency, reduced costs, and improved security in transactions through this integration. Acknowledging potential challenges such as AI decision-making implications and technical hurdles, the article advocates for ongoing research and development. It highlights the need for responsible AI adoption to maximize benefits while addressing concerns like algorithmic biases and potential market manipulation. Also explores AI's role in risk management, fraud detection, and investment management within the financial sector. It underscores the importance of ethical considerations, transparency, and accountability to ensure AI's integration aligns with the best interests of all stakeholders. As the article concludes, it emphasizes the dynamic and transformative potential of the integration of AI into blockchain and the cryptocurrency market. It advocates for a collaborative approach among stakeholders, policymakers, and developers to ensure responsible usage, compliance with regulations, and ongoing innovation. The synthesis of AI and blockchain technologies has the potential to revolutionize industries, enhance security, and contribute to a more efficient, transparent, and innovative future.
Persuasive Faculty and Rhetorical Structure Analysis of Popular Filipino Fiction Book Blurbs from 1980 – Present

Blurbs, being a subtle yet powerful pitch that influence readers to pick-up a book, might contradict the old adage ‘You cannot judge a book by its cover’. People do get influenced by blurbs (Schaefer &amp; Nelson, 2012). And they provide a vista of writing styles, a rhetoric that not only appeals to readers’ senses, but also resonates the cultural or socio-political ideals of a population at a given decade, which Küçüksakarya (2015) calls “contextually motivated language choices”. A local study, for instance, has forwarded that in the Philippines, culture greatly influences the way of writing (Pariña, 2010), and is a potent factor for persuading people to read. The style of blurb writing for Filipino fiction books, however, still remains unexplored, which is why this study is conducted. Anchored on Gea-Valor’s (2005) textual strategies to analyze twenty (20) blurbs of fiction books gathered from Goodreads – five each from decades 1980, 1990, 2000, and 2010 to present, findings showed that Filipino fiction book blurbs are more informational, than promotional. Albeit present in all decades, the blurbs in the following decades also focus on culture and romance. Utilizing Maan and Thompson’s (1986) Rhetorical Structure Theory, the analyses reveal that most blurbs entrench the plot to the potential readers, weaving both the informative and promotional intent of the blurbs. Filipino blurb writers more commonly use positive evaluative adjectives, superlatives, intensifiers, elliptical structure, personal pronouns like ‘we’, ‘us’, and ‘ours’ including rhetorical questions and imperatives directed towards readers, which help establish the Filipino’s communal culture, or the interconnectedness of ‘pakikisama’, which Pariña (2010) noted as one of the features of Filipino writing. The researchers recommend looking into the rhetorical structure and other presentational schemes of blurbs used as virtual advertising to shed light on this growing inquisitiveness towards this genre.
Pengembangan E-Learning Moodle Berbasis Virtual Private Server (VPS) Untuk Meningkatkan Hasil Belajar Pengetahuan Peserta Didik di Tengah Pandemi Covid-19 Pada Mata Pelajaran Geografi (Studi Kelas XI SMA Negeri 1 Teras Boyolali Tahun Ajaran 2020/2021)

&lt;p&gt;&lt;em&gt;The research aims to: &lt;/em&gt;&lt;em&gt;(1) to determine the feasibility of e-learning moodle based on Virtual Private Server to improve student learning outcomes; (2) determine the effectiveness of e-learning moodle based on Virtual Private Server to improve student learning outcomes;&lt;/em&gt;&lt;em&gt; (3) to determine the effect of e-learning moodle on learning outcomes in the knowledge section of students. The method used in this research is research and development. The research subjects were theory experts, media experts, teachers, and students in class XI IPS 1,2, and 4. The data collection instruments used theory expert validation sheets, media expert validation sheets, teacher assessment sheets, student assessment sheets, and tests and documentation.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt;The results of this study are: (1) e-learning moodle based on Virtyal Private Server is declared feasible based on theory expert judgment, teacher assessment, and student assessment by getting a score mode of 5 (excellent category on a Likert scale), as well as an assessment from media experts with score mode 4 (good category in Likert Scale); (2) e-learning Moodle based on Virtual Private Server is more effective in improving the learning outcomes of students' knowledge based on the higher class average on the cognitive pretest and posttest results that is 55.45 to 88.36 compared to MS Teams media where the class mean pretest results and cognitive posttest that is 53.56 to 76.88; (3) e-learning moodle based on Virtual Private Server has a significant effect on the learning outcomes of students’ knowledge with a Sig (2-tailed) value of 0.000 where 0.000 &amp;lt;0.05 so that there is a significant difference in the average towards student learning outcomes for the pretest and posttest scores in the experimental class.&lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;em&gt; &lt;/em&gt;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;&lt;em&gt;Keywords:&lt;/em&gt;&lt;/strong&gt;&lt;em&gt; Media Development, Virtual Private Server-based Moodle E-Learning, Learning Outcomes of Students' Knowledge&lt;/em&gt;&lt;/p&gt;
INVESTIGATING THE ESSAY WRITING CHALLENGES EXPERIENCED BY STUDENTS AT BINA SARANA INFORMATIKA UNIVERSITY

The study of writing has become an essential contributor to language learning research. Over the years, the existence of writing has led students to gain competence in learning a language. Throughout the process, students might have problems and experience errors that hinder them from producing the written product, especially an essay. Therefore, this study aims to critically identify and evaluate the students’ problems in writing essays, especially at Bina Sarana Informatika University. The research was conducted using a close-ended questionnaire with 37 questions regarding essay writing problems. Four significant problems: plagiarism, grammatical errors, lexical difficulties, and lack of planning became the focus of this study. Moreover, a lack of confidence also becames one of the problems in writing an essay. The finding of this research was that students agreed that lexical difficulties become the most common problem while writing an essay, with an average of 2,92. Interestingly, with an average of 2,3, the least common problem wass a grammatical error. By seeing the results from 21 respondents, it wass evident that the main thing that hinders students’ performance in writing an essay wass the difficulty in using the appropriate words and dictions based on context&lt;p&gt; &lt;/p&gt;
The Role of AI in Creating Realistic and Engaging AR Pet Games: The Case of Niantic’s Peridot

This study aimed to identify the role of artificial intelligence (AI) in creating more realistic and engaging AR pet games focusing on Niantic"s Peridot as a case study. Peridot is an AR pet game that leverages AI techniques such as convolutional neural networks (CNN), computer vision and semantic segmentation. The study investigates whether AI techniques play a role in improving realism and player engagement in AR pet games. In order to answer the question of the study, a comprehensive approach which combined qualitative and quantitative data analysis was adopted. The findings of this study provide valuable insights to future game developers who seek to create realistic and engaging AI-enabled AR games.
BLENDED LEARNING: PELUANG DAN TANTANGAN PELAKSANAANNYA PADA SEKOLAH DASAR

This research aims to explore the opportunities and challenges in implementing blended learning in elementary schools in Samarinda during the new normal period, using library research or literature review methodology. The main focus is to provide a comprehensive understanding of how blended learning can be implemented effectively, taking into account factors such as infrastructure readiness, teacher competency, and student engagement and motivation. The research results show that implementing blended learning in elementary schools offers valuable opportunities such as greater personalization of learning, development of student independence, integration of active learning through a combination of in-class and online methods, improvement of students' technology skills, and flexibility in accessing materials. However, this method also faces significant challenges, including limited access to technology among students, the need for more intensive teacher training, challenges in motivating students, and difficulties in assessing learning and ensuring the quality of online materials. The conclusions of this study underscore the importance of effectively addressing these challenges to create a conducive learning environment. Strategies that involve improving technological infrastructure, continuous teacher training, development of quality learning materials, and effective motivational approaches for students are needed.
Exploring Institutional Factors Affecting College Retention Using RandomForest Technique: Capital and Non-Capital Region

This study analyzed institutional factors affecting college student retention rates using a machine learning predictive model. The data of 2022, 2021, and 2022 university information disclosure data consisting of all four-year universities, capital region, and non-capital region were analyzed with the randomForest algorithm in R. First, the study findings indicate that the randomForest model demonstrated an accuracy rate of approximately 70%. Second, 10 key variables were identified in the overall university data set and 9 key variables in the capital region and non-capital region university data sets. However, there were some differences in the composition and ranking of the key factors in the data sets. Third, the partial dependence plots reveal the value ranges of the variables where the retention rate either decreased or remained stable. Institutions may apply these results by utilizing randomForest machine learning techniques for data-driven decision-making in formulating university retention policies.
Towards a Novel Hybrid Fuzzy Logic-Based Control Strategy to An Inverted Pendulum System

The current study proposes a new solution with a successful control method to balance an inverted pendulum placed on a cart. The control plant is a nonlinear drive system consisting of a freely rotating rod and a small moving 4-wheel vehicle. A novel control strategy is created as a reasonable integration between a fuzzy logic structure built up depending on the Lyapunov stability theory and the Particle Swarm Optimization (PSO) algorithm. The Lyapunov theory has long been known for designing effectual control schemes. Meanwhile, the PSO mechanism, one of the most famous and efficient optimization methods, determines three scaling factors in the control diagram. Various simulation results of the proposed hybrid fuzzy logic controller in four scenarios have been successfully obtained using MATLAB/Simulink software, outperforming several existing counterparts, namely conventional PID, PD- and PI-like fuzzy logic regulators. Promising findings in this study verify the applicability of the proposed control methodology in both theoretical and practical aspects.
Aquila Optimization Algorithm with Advanced Learning Model-Based Sentiment Analysis on Social Media Environment

Sentiment Analysis (SA) on social media is a text mining method that includes employing Natural Language Processing (NLP), and Machine Learning (ML) approaches to categorize and assess the opinions, attitudes, and emotional tone expressed in user-generated content on platforms including Instagram, Twitter, and Facebook. This analysis provides meaningful information for researchers, marketers, and businesses to track trends, gauge public sentiment, and make datadriven decisions by automatically classifying text as positive, negative, or neutral, which helps them understand brand perception, customer satisfaction, and emerging problems in the dynamic world of online communication. Deep Learning (DL) based SA on social networking media is a robust NLP tool that leverages neural networks, including Recurrent Neural Network (RNN) or transformer models such as GPT and BERT, to automatically define the sentiment expressed in usergenerated content on platforms like Facebook, Twitter, and Instagram. This manuscript offers an Aquila Optimization Algorithm with Deep Learning based Sentiment Analysis and Classification (AOADL-SAC) technique on social networking. The AOADL-SAC technique aims to recognize and classify the sentiments on social media. In the presented AOADL-SAC technique, pre-processing was implemented to convert the data provided as input into a compatible format. In addition, the AOADL-SAC technique implements a Long Short-Term Memory (LSTM) approach for recognizing and classifying sentiments. At last, the AOA-based tuning procedure was performed to adjust the hyperparameters of the LSTM approach. The investigational output of the AOADL-SAC technique is examined on a standard dataset. The comprehensive outputs highlighted the AOADL-SAC method and stated the AOADL-SAC technique accomplishes better outcomes than recent techniques concerning distinct aspects.
TEXT MINING: CLUSTERING USING BERT AND PROBABILISTIC TOPIC MODELING

In order to find significant patterns and fresh ideas, free-form content is transformed into structured format using a process known as text mining or text data mining. It enables businesses to easily locate important information in texts like emails, social media posts, support requests, chatbots, and other sorts of text. Text mining enables businesses to anticipate possible threats from rivals, react quickly to production or delivery problems, and provide more individualised customer service. Businesses employ text mining for a range of functions, including production, IT, marketing, sales, and customer service. By carefully examining the phrases used in the source texts, topic modelling aims to pinpoint the recurrent themes in a corpus. These concepts are known as “topics”. As a result, textual data may be measured and used in quantitative analysis. In this sector, there are several subject modelling kinds that differ from one another based on a few unique traits and criteria. In our paper we have represented mainly 3 types of topic modelling techniques namely Latent Semantic Analysis (LSA), Hierarchical Dirichlet Process (HDP), and Latent Dirichlet Analysis (LDA) and calculated the coherence score of each method and compared them. And we have infused the concept of BERT with this topic modelling models and proposed a new model called HDP BERT and calculated the coherence Score and clusters the topics. At the end the n-grams features are applied to all 4 models and compared among each other in bases of uni, bi and trigram rate percentage.
Using Artificial Intelligence for Education in the Education 5.0 Era to Improve Reading Skills

This research aims to determine the use of ChatGPT for education in the Education 5.0 era in improving reading skills. ChatGPT can answer questions humanely, just like Google Nest; only Google Nest requires machines or tools like regular Google. This research uses quantitative methods, data obtained through interviews, and questionnaire distribution. Distribution of questionnaires using Google forms. The research results show that using ChatGPT for education in the Education Era 5.0 can benefit students, as evidenced by increased reading skills. From this research it can concluded that the use of ChatGPT for education has proven to be effective and efficient, the research proves this results that 80% of students have the highest scores. The limitation of this research is that the researcher only researched the use of ChatGPT for education in the Education Era 5.0 even though there are still many uses of other media that can be used as alternatives in improving students' reading skills.
Penerapan Logika Fuzzy Mamdani Untuk Menentukan Stok Beras Di Toko Anugrah Jaya Cirendeu Berbasis Web

Abstract&#x0D; Rice is a very strategic food ingredient. Rice as a food ingredient is still a basic need, so the need for rice is greater than the need for industrial rice. Compared to other staple foods, national rice consumption is relatively large, so that it can be distributed evenly in sufficient quantities and is affordable by the community, increasing income for rice selling entrepreneurs. In every shop selling rice, of course, there are many problems. The problem that is often experienced is that the amount of availability is insufficient or out of stock. Each shop is definitely required to maintain the availability of sufficient stock so that sales in the store run smoothly, Fuzzy Mamdani is more specific, which means that this method pays more attention to the conditions in each Fuzzy area. So that Fuzzy Mamdani will produce decisions that are faster and more accurate. This study aims to help recommend ordering rice stock so that the stock is always available in sufficient quantities, so as to facilitate sales.&#x0D; Keywords: Determination of Rice Stock, Rice, Fuzzy Mamdani
FORENSIC ACCOUNTING SKILLS REQUIRED BY ACCOUNTING EDUCATION GRADUATES FOR EFFECTIVE ACQUISITION OF FRAUD DETECTION SKILLS

The study was carried out to identify forensic accounting skills required by accounting education graduates for effective acquisition of fraud detection skills in universities in Cross River State. Nigeria. It also investigated the extent to which forensic accounting education can enhance the acquisition of fraud detection skills among accounting students. The study adopted a descriptive survey design. The population of the study consisted of all accounting educators in public universities in Cross River State and all senior accountants in the 39 government ministries in Calabar. This brought the total population of accounting educators to 30 and that of accountants to 108. Census method was adopted as the sampling technique for the accounting educators while purposive sampling technique was adopted for the accountants. Data were collected using a researcher-made questionnaire which was validated by a research expert in accounting and a business educator. Copies of the questionnaire were administered to the respondents. The completed copies returned were 22 copies for the accounting educators and 96 for the accountants. It was this number that was used in generating data used for the answering of the research questions. Data collected from the respondents were analyzed using descriptive statistics of mean and standard deviation; also, the hypotheses formulated were tested using independent-t-test statistic at 0.05 level of significance. The results revealed that areas of forensic accounting be included in the curriculum of accounting education because it can enhance the acquisition of fraud detection skill. It was recommended that forensic accounting education be introduced into the accounting education curriculum.