Reviewerly/exHarmony huggingface dataset:
I would love this to be like an assistant, not the teacher: a voice of  the customer perspective of what distance learning students want from an  Artificial Intelligence Digital Assistant

With the release of Generative AI systems such as ChatGPT, an increasing interest in using Artificial Intelligence (AI) has been observed across domains, including higher education. While emerging statistics show the popularity of using AI amongst undergraduate students, little is yet known about students' perceptions regarding AI including self-reported benefits and concerns from their actual usage, in particular in distance learning contexts. Using a two-step, mixed-methods approach, we examined the perceptions of ten online and distance learning students from diverse disciplines regarding the design of a hypothetical AI Digital Assistant (AIDA). In the first step, we captured students' perceptions via interviews, while the second step supported the triangulation of data by enabling students to share, compare, and contrast perceptions with those of peers. All participants agreed on the usefulness of such an AI tool while studying and reported benefits from using it for real-time assistance and query resolution, support for academic tasks, personalisation and accessibility, together with emotional and social support. Students' concerns related to the ethical and social implications of implementing AIDA, data privacy and data use, operational challenges, academic integrity and misuse, and the future of education. Implications for the design of AI-tailored systems are also discussed.
Extracting Lexical Features from Dialects via Interpretable Dialect  Classifiers

Identifying linguistic differences between dialects of a language often requires expert knowledge and meticulous human analysis. This is largely due to the complexity and nuance involved in studying various dialects. We present a novel approach to extract distinguishing lexical features of dialects by utilizing interpretable dialect classifiers, even in the absence of human experts. We explore both post-hoc and intrinsic approaches to interpretability, conduct experiments on Mandarin, Italian, and Low Saxon, and experimentally demonstrate that our method successfully identifies key language-specific lexical features that contribute to dialectal variations.
Profile of Rainfall Patterns and Extreme Air Temperatures 1981-2020 in the Mosunal Region of Indonesia (Case Study: South Sumatra)

Increasing concentrations of greenhouse gases have led to changes in extreme climate events. This study aims to describe the picture of climate change in the South Sumatra Region during the last 40 years, namely from 1981-2020. Rainfall and extreme temperature data were obtained from BMKG data for South Sumatra Province at the Palembang City Climatology Station (SK Palembang City) and the Sultan Mahmud Badaruddin II Meteorological Station (SM SMB II). Maximum temperature data, minimum temperature and rainfall were obtained based on parameter profiles obtained from BMKG data for South Sumatra Province based on the ETCCDMI provisions. Maximum temperature data, minimum temperature and rainfall are processed with RClimDex software so that temperature and extreme rain index data are obtained. These indices are extreme climate indices consisting of TN90p, TX90p, TNn, TNx,TXx, TXx, TMAXmean, TMINmean, RX1day, RX5day, SDII, CDD and CWD. The results of this study indicate that the trend of air temperature will increase significantly in South Sumatra Province, especially the minimum air temperature, then the precipitation pattern will also increase, especially the accumulation of rainfall for 5 consecutive days. There is an increase in the number of dry days and a decrease in the number of wet days, as well as the higher accumulation of daily rainfall but the wet days are decreasing day by day. This is also increasingly having an impact on climate change in South Sumatra Province which is getting hotter day by day and the smoke disaster due to land and peat fires in South Sumatra Province is increasingly worrying.
PERFORMANCE EVALUATIONS OF THE MANTA RAY FORAGING OPTIMIZATION ALGORITHM IN REAL-WORLD CONSTRAINED OPTIMIZATION PROBLEMS

Metaheuristic algorithms are often preferred for solving constrained engineering design optimization problems. The most important reason for choosing these algorithms is that they guarantee a satisfactory response within a reasonable time. The swarm intelligence-based manta ray foraging optimization algorithm (MRFO) is a metaheuristic algorithm proposed to solve engineering applications. In this study, the performance of MRFO is evaluated on 19 mechanical engineering optimization problems in the CEC2020 real-world constrained optimization problem suite. In order to increase the MRFO performance, three modifications are made to the algorithm; in this way, the enhanced manta ray foraging optimization (EMRFO) algorithm is proposed. The effects of the modifications made are analyzed and interpreted separately. Its performance has been compared with the algorithms in the literature, and it has been shown that EMRFO is a successful and preferable algorithm for this problem suite.
MODERN FORMS OF LIBRARY ORGANIZATION IN THE ACTIVITY OF PARENTS AND EDUCATORS

This article talks about the reforms aimed at the development of reading from childhood, the responsibility of parents in raising children, the role of the family and preschool education organizations in the education of the young generation as a well-rounded person.
The Impact of International Conflicts on the Cryptocurrency Market: The Case of Israel–Palestine Conflict

In the financial markets, international conflicts have a crucial influence. The ongoing conflict between Israel and Palestine is one of them which poses hazards to international politics and the economy. This study is the first study that examines the potential influence of the Israel-Palestine conflict on the cryptocurrency market. To this end, the event study methodology is used for the period 01.03.2023 – 17.10.2023, and the top ten cryptocurrencies are chosen for analysis based on their market capitalization. The results show that although the Israel-Palestine conflict affected certain cryptocurrencies (including BTC, TRX, SOL, and ETH), it had no statistically significant effect on the market as a whole. Furthermore, the majority of the effect was statistically positive, which may be an indication that the cryptocurrency market is considered a safe haven. Moreover, the abnormal returns were usually recorded in the days before the event, suggesting that the event had been anticipated by some cryptocurrencies. Investors and financial analysts may benefit from these results by considering the cryptocurrency market as an alternative investment tool in these uncertain times and using these findings to diversify their portfolios and create hedging strategies.
Evolution and Efficiency in Neural Architecture Search: Bridging the Gap  Between Expert Design and Automated Optimization

The paper provides a comprehensive overview of Neural Architecture Search (NAS), emphasizing its evolution from manual design to automated, computationally-driven approaches. It covers the inception and growth of NAS, highlighting its application across various domains, including medical imaging and natural language processing. The document details the shift from expert-driven design to algorithm-driven processes, exploring initial methodologies like reinforcement learning and evolutionary algorithms. It also discusses the challenges of computational demands and the emergence of efficient NAS methodologies, such as Differentiable Architecture Search and hardware-aware NAS. The paper further elaborates on NAS's application in computer vision, NLP, and beyond, demonstrating its versatility and potential for optimizing neural network architectures across different tasks. Future directions and challenges, including computational efficiency and the integration with emerging AI domains, are addressed, showcasing NAS's dynamic nature and its continued evolution towards more sophisticated and efficient architecture search methods.
Temporal-Spatial Processing of Event Camera Data via Delay-Loop  Reservoir Neural Network

This paper describes a temporal-spatial model for video processing with special applications to processing event camera videos. We propose to study a conjecture motivated by our previous study of video processing with delay loop reservoir (DLR) neural network, which we call Temporal-Spatial Conjecture (TSC). The TSC postulates that there is significant information content carried in the temporal representation of a video signal and that machine learning algorithms would benefit from separate optimization of the spatial and temporal components for intelligent processing. To verify or refute the TSC, we propose a Visual Markov Model (VMM) which decompose the video into spatial and temporal components and estimate the mutual information (MI) of these components. Since computation of video mutual information is complex and time consuming, we use a Mutual Information Neural Network to estimate the bounds of the mutual information. Our result shows that the temporal component carries significant MI compared to that of the spatial component. This finding has often been overlooked in neural network literature. In this paper, we will exploit this new finding to guide our design of a delay-loop reservoir neural network for event camera classification, which results in a 18% improvement on classification accuracy.
Beyond Cryptic Equations: Reimagining Concepts in Physics Through Metaheuristics and Fantasy Stories using Neutrosophic Venn Diagram

Physics, the grand narrative of the universe, has long been viewed as a realm of cold, hard equations. But what if we looked beyond the formulas and considered a more imaginative origin for some of its concepts? This article explores the intriguing possibility that physics, and even cosmology, might share a surprising kinship with metaheuristics and fantastical fiction. Metaheuristics, a branch of computer science, deals with finding approximate solutions to complex problems. Perhaps the universe, in its vastness, employs a set of "rules" that lead to the most likely outcomes, much like an algorithm searching for the best solution within a vast space of possibilities. The connection strengthens when we consider the fantastical. Argentine writer Jorge Luis Borges, known for his thought-provoking short stories, often explored themes of infinity, labyrinths, and forking realities. In this article, we discuss, among other things, how to look at physics laws from an alternative fundamental viewpoint that is fluid dynamics perspective. As an example, we provide an outline for deriving the Newton gravitational law from the Kutta-Joukowski theorem, and then deriving the Kutta-Joukowski theorem from Bernoulli principles. In the meantime, it is known that vortex flows, related to solar convective turbulent dynamics at granular scales and their interplay with magnetic fields within intergranular lanes, occur abundantly on the solar surface and in the atmosphere above.
Characteristics of Marketing Activities of Non-Profit Entities (Advertising and Pr in Scientific Libraries)

Non-profit activities, depending on their nature, engage in advertising activities and do not pursue profit-making purposes in this activity. This approach gives rise to different thoughts for state educational institutions, cultural institutions and libraries. When organizing the activities of libraries, completely different methods and forms are used depending on their type and type. In recent years, depending on its goals and objectives, the library has begun to widely use modern PR technologies in organizing its work. Higher education libraries express their function as a research library in different ways. In the article we analyze the activities of leading scientific and university libraries and try to determine the general aspects of the organization of PR activities in these types of libraries. An attempt has been made to formulate a scientific-experimental model with the aim of obtaining modern PR effects through the use of both traditional and modern technologies.
The Practical Exploration of Information-based Teaching in Chinese Teaching in Secondary Vocational Schools

Our country's science and technology is more and more developed, information technology is widely used in our life aspects, education is no exception, this for the secondary vocational school language teaching to modernization, closely follow the trend of The Times development is an opportunity, secondary vocational educators should seize the opportunity to realize the reform of vocational teaching. Chinese is the mother tongue of our country and the crystallization of our traditional culture and ancient wisdom. Students must learn it to strengthen their own reserves of Chinese knowledge. Chinese is one of the compulsory cultural courses carried out by schools.
Strategies for Integrating Ideological and Political Education Elements into Courses for English Majors through Generative AI: A Case Study of Comprehensive English Course

This paper explores the strategies for integrating ideological and political education (IPE) elements into courses for English majors through the use of generative artificial intelligence (AI). Through a case study of the comprehensive English course, this paper examines how generative AI can facilitate the incorporation of IPE elements into English majors’ education. Various strategies are proposed to effectively integrate IPE elements into the curriculum, enhancing students' ideological and moral education while fostering language proficiency.
Beliefs on Second Language Learning among Pre-service Teachers in a Public University in Malaysia

The purpose of this research was to identify the Teaching of English as a Second Language (TESL) pre-service teachers’ beliefs about second language (L2) learning, to determine whether there is a significant difference in beliefs among the TESL pre-service teachers of different years of study and how these beliefs were formed. These are important as the pre-service teachers’ beliefs would have a direct influence on their practices as a teacher in future. This research was conducted with a sample size of 113 respondents using a mixed method design. Data collection is using the Belief About Language Learning Inventory, often known as BALLI approach to ensure a comprehensive understanding of individuals' beliefs. In addition, data was gathered using semi-structured interviews thus, guaranteeing a more in-depth understanding of the participants' experiences and beliefs. Descriptive statistics showed that the highest mean score was recorded for the “motivation and expectations” dimensions. The ANOVA results showed statistically significant difference in the mean scores amongst the different years of study. Interview results indicated that beliefs were dominantly influenced by social support and exposure to the L2, and intrinsic and extrinsic motivation. Results of the study could inform course developers and lecturers as to which aspects of language learning and pedagogical knowledge need to be focused on in the pre-service teachers’ curriculum.
PENGOLAHAN FOTO UDARA UAV (UNMANNED AERIAL VEHICLE) MENGGUNAKAN SOFTWARE AGISOFT METASHAPE

This research aims to explain the method of utilizing UAV (Unmanned Aerial Vehicle) for aerial data photography and processing of UAV aerial photos using Agisoft Metashape software. In this context, the author will discuss the key steps in data processing, including aerial photo preprocessing, 3D model generation, digital elevation model (DEM) extraction, orthomosaic extraction, and the provision of processing information from the aerial photo data. The research flow is structured in a series of steps, encompassing all stages performed during the research process, allowing for a clear direction of the research's progression. The final results, in the form of DEM and orthomosaic, hold significant value in mapping and geospatial analysis. This research is expected to enhance the understanding of UAV usage in surveying and mapping, enabling broader applications in various sectors. Careful supervision and control of UAV flights are highly emphasized to ensure data quality. The use of UAVs and Agisoft Metashape opens up new opportunities for accurate, efficient, and effective surveying and mapping.
BIBLIOMETRIC MAPPING PUBLICATIONS OF SCIENTIFIC WORK OF INFORMATION SYSTEMS LECTURER AT UIN SYARIF HIDAYATULLAH JAKARTA ON GOOGLE SCHOLAR SYSTEMATIC REVIEW USING RESEARCH RABBIT

ABSTRACT&#x0D; In the modern era dominated by technology, understanding academic developments in the Information Systems Department of UIN Syarif Hidayatullah Jakarta through Google Scholar and Research Rabbit is very important. The research focuses on identifying lecturers' research interests, with the aim of developing a more relevant curriculum for students. Literature studies are used to collect and analyze information from various sources. The research results reveal the latest research topics that lecturers publish, becoming the basis for future research and guidelines for curriculum development according to technological developments. The conclusion emphasizes the importance of adapting research to technological developments and a deep understanding of lecturers' interests to maintain the relevance of the curriculum in an ever-changing academic world. This step is key in preparing students to succeed in a rapidly developing environment. In this context, lecturers' understanding and research helps shape a curriculum that is able to face the challenges of modern technology and produce graduates who are ready to face continuous change.&#x0D; Keywords : Bibliometrics, Publications, Scientific Work, Google Scholar, Research Rabbit
A Study on the Differences in Quantity and Quality of Student Response Writings Between Reading Text and Watching Video: Focusing on the classic ‘The Old Man and the Sea’

Thnemedia.
Case study on core competency-centered &lt;College Writing&gt; class operation: Focusing on Dankook University class cases

Thilities.
Undergraduate International Students’ Use of Online Machine Translation and Instructor Perceptions － Focusing on Korean Writing

Thies
Writing Education for Sutainable Life: Focusing on the Possibility of Reflection and Value of Communication through writing

Thisners.
Review of Essay for Teaching Profession in Elementary School Teacher Recruitment Examination: A Multiple Document-based Knowledge Construction Process

Thises.
Exploration of Improvements for the Operation of General Education Courses at the Buddhist Missionary University : Focusing on the Course 'Buddhism and Humanity'

This study explores the necessity and improvement directions for implementing the educational philosophy in the common liberal arts course, 'Buddhism and Humanity.' Based on the related survey results, an attempt was made to analyze the findings and propose suggestions for the improvement of operational methods. In the analysis results, students consistently recognized the need for changes in the overall operation of the 'Buddhism and Humanity' course and had a clear understanding of the reasons and directions for improvement. Based on these results, the following recommendations are proposed: Firstly, to reflect practical and realistic aspects in the organization of lecture content, internalizing Buddhism as cultural knowledge and supplementing lecture materials to generate interest. Secondly, to foster a self-directed and voluntary learning atmosphere and improve teaching methods. Thirdly, to improve the structure of lectures and evaluation methods. Lastly, to provide guidance and promotion for innovative teaching methods.
A Multi-Metric Model for analyzing and comparing extractive text summarization approaches and algorithms on scientific papers

In today's world, where data and information are increasingly proliferating, text summarization and technologies play a critical role in making large amounts of text data more accessible and meaningful. In business, the news industry, academic research, and many other fields, text summarization helps make quick decisions, access information faster, and manage resources more effectively. Additionally, text summarization research is conducted to further improve these technologies and develop new methods and algorithms to provide better summarization of texts. Therefore, text summarization and research in this field are of great importance in the information age. In this study, a new operating model for text summarization that can be applied to different algorithms is proposed and evaluated. Sixteen summarization algorithms covering six approaches (statistical, graph-based, content-based, pointer-based, position-based, and user-oriented) were implemented and tested on 50 different full-text article datasets. Four evaluation criteria (BLEU, Rouge-N, Rouge-L, METEOR) were used to assess the similarity between the generated summaries and the original summaries. The performance of the algorithms within each approach was averaged and the overall best-performing algorithm was selected. This best algorithm was subjected to further analysis through Topic Modelling and Keyword Extraction to identify key topics and keywords within the summarised text. The proposed model provides a standardized workflow for developing and thoroughly testing summarization algorithms across datasets and evaluation metrics to determine the most appropriate summarization approach. This study demonstrates the effectiveness of the model on a variety of algorithm types and text sources.
Gender and Age Estimation By Image Processing

Today, with the increasing interest in technology, very useful studies are carried out in the field of image processing. Image technologies are also used in many fields such as security, defense, medicine, and industry. In this study, age, gender, and ethnicity were found in the image by using different deep learning techniques and by building our own model in CNN. The 23705 images taken from the csv file named Face Data taken from Kaggle were categorized as different gender, race, and age within the application and the accuracy and losses of the results were transferred with graphs. In addition, by creating an interface with the help of the Python flask library, the results of the snapshot taken from the camera (age, gender, and race) can also be found. Out of the 23705 images, approximately 12000 male and 11000 female profiles were obtained. These profiles were classified according to 5 different genetics specified in the dataset. The genetics in the application (0 represented White, 1 represented Black, 2 represented Asian, 3 represented Indian, 4 represented Others.) The most difficult part of this study is that the picture changes depending on many factors such as posture, pose angle, brightness, and resolution at the time of shooting..
Computing Longest Common Subsequence under Cartesian-Tree Matching Model

Two strings of the same length are said to Cartesian-tree match (CT-match) if their Cartesian-trees are isomorphic [Park et al., TCS 2020]. Cartesian-tree matching is a natural model that allows for capturing similarities of numerical sequences. Oizumi et al. [CPM 2022] showed that subsequence pattern matching under CT-matching model can be solved in polynomial time. This current article follows and extends this line of research: We present the first polynomial-time algorithm that finds the longest common subsequence under CT-matching of two given strings $S$ and $T$ of length $n$, in $O(n^6)$ time and $O(n^4)$ space for general ordered alphabets. We then show that the problem has a faster solution in the binary case, by presenting an $O(n^2 / \log n)$-time and space algorithm.