Reviewerly/exHarmony huggingface dataset:
The Image of Women’s Novels in Nusantara Children’s Series and Their Benefits as High School Teaching Materials

This research aims to describe the image of women in the Anak Nusantara novel series by Tere Liye and the benefits of the novel as teaching material. This research departs from the phenomenon of the use of old novels which are no longer relevant for use as teaching materials today. This research uses descriptive qualitative research methods with a feminist approach. Data collection was carried out using literature study, reading techniques, and note-taking techniques. The validity of the data that has been obtained will be tested by triangulation, diligent observation, and member checking. After that, the data will be analyzed using the Miles &amp;Huberman model analysis technique (data reduction, data presentation, and conclusion). The research results concluded that the Anak Nusantara novel series by Tere Liye contains the image of a woman who is obedient to God, cares about the environment &amp; uses nature, disciplined, firm, loving, protective, persistent, high social spirit, devoted to the parents, smart, skilled, multitasking, brave, responsible, honest, exemplary, and successful. The entire image of women in the novel is a positive representation of women who can be used as role models for students. Furthermore, the novel series is suitable for use as teaching material because it meets the criteria for quality non-text books and fiction books.
Enhancing Content Development in EFL Students' Writing: Leveraging the Four-Square Writing Method

Effective writing skills are vital for students' development as proficient communicators and critical thinkers within the realm of education. Nevertheless, numerous students encounter difficulties when it comes to content development in their writing. This study endeavors to enhance students' content development in writing, a foundational skill essential for fostering effective communication and critical thinking. The research assesses the efficacy of the Four-Square Writing Method in improving writing content among EFL students at MAN 1 Parepare, an Islamic state senior high school in South Celebes, Indonesia. Using a pre-experimental methodology with a one-group pretest-posttest design, 18 EFL students from class XI IPA 2 were selected through cluster random sampling. Data were collected through written tests before and after the intervention and analyzed using Data Analysis of Microsoft Excel. The results demonstrate a significant improvement in students' writing content at MAN 1 Parepare, with average scores increasing from 59.44 (fair) to 89.63 (very good). A t-test revealed a substantial difference between pretest and posttest scores, with a t-value of 15.46, surpassing the critical t-table value of 2.11. These findings indicate that the Four-Square Writing Method effectively addresses content development challenges in student writing, highlighting its potential as an alternative teaching method in diverse educational settings to enhance students' abilities in planning, organizing, and developing written content.
Государственная политика по отношению к высшей школе: историко-политологический анализ

The article is considering the problem of the state policy development in the field of scientific research at universities, with a focus on scientific and technological progress. The paper analyzes of university science evolution throughout its historical stages, starting with the creation of the first higher education institutions in Russia in the 17th&nbsp;century. Then the author considers the Soviet vision and interpretation of scientific and technological progress with an emphasis on the influence of political ideology on scientific activity, followed by a period of changes in the structure of universities in the 1990s and a way out of the crisis in the modern context. The paper studies modern world trends in detail. They are related to the increasing role of universities in the innovative and scientific-technical development of the economy. The author analyzes the experience and specifics of the university’s development to assess the contribution of higher education institutions in other countries at the same level. As a result, the collected material makes it possible to understand the current level of higher education development and provides an opportunity to predict the prospects for the university science development in real time.
Prediction of Elementary School Students' Mental Health using Decision Tree Algorithm with K-Fold Cross-Validation in Bone Bolango Regency, Gorontalo Province

Mental health is a fundamental component of the World Health Organization's definition of health, encompassing not only freedom from illness but also well-being in physical, mental, and social dimensions. In today's modern society, mental health has become a paramount issue, as its soundness enables individuals to realize their own potential, cope with normal life pressures, work productively, and contribute effectively to their communities. In Indonesia, mental health-related challenges are associated with the absence of a reliable mental health detection tool. Conversely, abroad, there has been a substantial amount of research focused on innovative technology-based mental health detection using Machine Learning. This study aims to predict mental health using the Social Emotional Health Survey-Secondary (SEHS-S) as the evaluation criterion for prediction through Machine Learning. The Decision Tree algorithm is employed, and the prediction model is tested using K-Fold Cross-Validation, resulting in 8 folds with an accuracy rate of 78.61%.
Innovative Design of Solar Benches for Public Spaces: Renewable Energy with Arduino Integration

This research aims to design and implement an innovative park bench that combines solar panel technology with the Arduino platform. The methodology of this research consists of designing the integration of solar panels with Arduino components that are assembled integrated on the physical bench. In the analysis phase, measurements of solar energy production were conducted under various light and weather conditions. The performance of the system in battery charging and fulfillment of energy needs was evaluated. Environmental data from Arduino sensors were analyzed to illustrate the effect of environmental conditions on system operation. The results showed that the solar bench produced higher energy during daytime and reduced during nighttime conditions. The system can supply energy for purposes such as lighting and charging electronic devices. The voltage and current data at night show inefficiency in charging the solar panel, while the cell phone charger condition works as long as the battery is above 15%. In addition, environmental analysis through Arduino sensors revealed a correlation between light intensity and energy production and usage. These findings can be used to optimize the operation of the smart bench system based on changing environmental conditions. In conclusion, this solar bench design has the potential to reduce environmental impacts and support the use of renewable energy in urban public spaces, with the potential to increase public awareness of sustainable energy
The Significance of Philosophical Anthropology in Determining the Methodology of Modern Scientific Research

Purpose. This research involves revealing the methodological significance of the anthropological understanding of values for conducting modern scientific research. Theoretical basis. Philosophical anthropology acts as an epistemological basis for answers to ontological questions that are part of the structure of such problems in modern science as the construction of a scientific picture of the world, the ordering of data of natural attitude, and anthropocosmism. The ontological basis for the formation of the anthropological theory of values is the teaching of Wilhelm Leibniz, Immanuel Kant, Rudolf Lotze, and Martin Heidegger. Originality. The creation of a scientific picture of the world, the research of natural attitude, and an anthropological approach to cosmology carried out from the viewing angle of the philosophy of values show the close mutual conditioning of these scientific issues. A successful determination of one’s value positions by a scientist-researcher is impossible without his/her agreeing with his/her picture of the world with the prevailing ideas about the world in their society. Such ideas are studied by anthropocosmism, which researches not so much the world in itself, but a view of this world from the standpoint of the existing state of society and the main intentions of its development. Conclusions. The value attitude of scientists at a certain stage of the development of scientific knowledge forms their picture of the world, which has the form of self-explanatory scientific provisions. The facts of modern physics must always, one way or another, receive their legitimation through the world of the human natural attitude. Even the unobservable characteristics of the microcosm are explained by appealing to knowledge about the observable characteristics of the world. The anthropocentric nature of cosmology is determined by the fact that in modern philosophy, the values of a person explain not only the way of one’s cognition but also the way of one’s inclusion in the world.
Artificial Intelligence as a Socio-Cultural Phenomenon: the Educational Dimension

Purpose. The study aims to understand artificial intelligence as a socio-cultural phenomenon and its impact on education, where the spiritual sphere of humanity, moral norms, values, and human cognitive abilities are preserved, transferred as well as reproduced. A new discourse on the interaction of artificial and authentic human intelligence becomes inevitable, which has led to a situation of uncertainty. Changes in the socio-cultural environment under the influence of artificial intelligence increase potential threats to the educational space, which stimulates to find the ways to eliminate them. Theoretical basis. Various approaches of classical and postmodern philosophical heritage were taken as a theoretical basis for the research. The originality of the study is in the interpretation of artificial intelligence as a modern form of alienation of essential human characteristics in the socio-cultural context of information technology. The expansion of artificial intelligence raises awareness of the existential threat to the basic socio-cultural, moral and ethical principles of humanism. It is proved that various forms of alienation in the current existing socio-cultural space are typical of our reality, which changes the system of values, moral principles, and social organization of the community. Conclusions. In conclusion, it is proved that AI is a natural stage of scientific and technological progress, which reflects its secondary, derivative nature from human (authentic) intelligence. Human intelligence will always have advantages over AI due to its ability to create, communicate socially and culturally, and be emotional. The dilemma of the counterbalance between human and artificial intelligence is perceived mainly at the emotional level of people. The millennial understanding of the primacy of the creator over his creation can traditionally overcome this contradiction. The universality of human thinking is an undeniable advantage of human intelligence and a guarantee of its, i.e. our, priority.
Spiritual and moral education of schoolchildren in the process of studying the subject area "Technology"

The article substantiates the relevance of spiritual and moral education, discusses the purpose, objectives, approaches, principles and conditions for the formation of spiritual and moral values among schoolchildren in the process of studying the subject area "Technology".
Specialist-Woman Interaction System for Female Empowerment in Cases of Discrimination and Gender Violence

Gender violence and discrimination against women in Peru persist as a pressing social issue, demanding prioritized attention. Despite ongoing efforts, the prevalence of gender violence remains stubbornly high. A significant challenge in addressing this problem lies in the delayed reporting by victims to authorities or support organizations. On average, victims in Peru take 8 years and 8 months to report their ordeal, influenced by factors like fear of the aggressor, lack of information about available resources, and distrust in the justice system. In response, an integrated system has been developed to facilitate communication and support for victims. Comprising a cloud web platform and a virtual assistant, this system provides a secure and anonymous space for victims to share their concerns. The virtual assistant, or chatbot, serves as an intermediary, aiding victims in expressing their concerns and delivering pertinent information. Validation tests revealed that over 90% of participating women approved the chatbot as an effective means of interaction for obtaining information and scheduling appointments with specialists. This positive reception indicates that the system effectively fulfills its purpose of offering an accessible and confidential communication channel. Moreover, collaborating specialists have acknowledged the benefits of the system, noting its facilitation of regular tasks and improvement in patient interaction. Communication through the chatbot enhances specialists’ understanding of victims’ needs, contributing to more effective support.
The advertising discourse of menstrual activism in the femcare industry

This research study aims to analyze how Peruvian women perceive the advertising discourse of menstrual activism in the femcare section of the Nosotras brand with the “Womb Stories” campaign. For this purpose, a qualitative research approach was used through semi-structured in-depth interviews with women aged 25 to 35 who belonged to online communities of feminism, maternity, sexuality and/or activism. As a result, the interviewees mentioned that the use of the advertising discourse of menstrual activism was positive in the category as it allowed to demystify menstruation, empower women, and reduce stigma around their bodies by presenting more real situations of menstruation and other aspects around it. However, brand advertising efforts would not yet be enough with respect to what the movement is seeking. Thus, it is necessary that brands that work with this type of advertising discourse take into account aspects such as the representation of menstruation, the representation of women, the handling of real stories and the use of visual resources that evidences the reality of everything that menstruation entails without falling into the menstrual stigma.
Design of a Crowdlending System for Formalized SMEs Based on Smart Contracts in Metropolitan Lima

In Metropolitan Lima, small and medium-sized enterprises (SMEs) face significant challenges in obtaining financing, primarily due to high interest rates and stringent requirements from traditional financial institutions. This research introduces a crowdlending system based on smart contracts backed by blockchain technology as a solution to these obstacles. A validation with end users was conducted, and the results obtained demonstrated an impressive compliance rate of 99%. This innovative approach provides a secure, transparent, and efficient environment, offering a robust solution to the financing needs of SMEs in the region.
Panorama of Peruvian Primary Education Teachers Trained in ICT Use before COVID-19 Pandemic

In order to determine the panorama of primary education teachers who received training in ICT use before the transition to e-teaching due to the covid-19 pandemic in Peru, this study is presented with a quantitative, descriptive and trending. For this, three Surveys to Peruvian Teachers (ENDO) carried out by Ministerio de Educación del Perú before the pandemic, in 2014, 2016 and 2018 were analyzed. The total of primary education teachers who participated in each year, respectively, were: 4334 (65.6 % = urban, 34.4 % = rural), 4336 (72.3 % = urban, 27.7 % = rural) and 6700 (76.5 % = urban, 23.5 % = rural). After the analysis, it can be concluded that number of teachers who received training on this subject in 2014 decreased in 2018, and that classroom-based modality is preferred by teachers surveyed to continue training on ICT use.
Prototype Guided Adversarial Domain Adaptation for Time Series Classification

Unsupervised Domain Adaptation (UDA) is a powerful solution to domain shift problems by transferring knowledge from labeled source domain to unlabeled target domain. Although UDA has gained much attention in visual applications, its exploration in time series has been relatively limited. In the paper, we propose a Prototype Guided Adversarial Domain Adaptation (PGADA) method to achieve UDA for time series classification. The method is designed based on a Teacher-Student architecture and uses an attention-based meta-network to transfer knowledge from teacher to student. Afterwards, a bi-classifier adversarial strategy is then used to align the source and target domains based on the student network. Meanwhile a prototype network generates prototypes to promote category-level alignment, in which the prototypes are gradually updated by more confident target samples. A bi-classifier achieves the category decision boundary adaptively adjusting to improve the classification performance on the target domain. We conduct the experiments on the practical time series datasets and show that the superiority of the proposed method.
Performance Evaluation of AVC and HEVC for E-Learning: Optimizing Quality and Reducing Bandwidth Usage

E-learning has experienced a surge in popularity, particularly during and after the COVID-19 pandemic. Online learning has proven to be a vital tool for students and educators to continue academic activities while adhering to social distancing guidelines and during the times of natural disasters that disrupt the conventional learning environments. It also offers accessibility to disabled students and those facing challenges to reach to the traditional learning. But due to increased demand, it is crucial to optimize cost of transmission while minimizing bandwidth usage while maintaining high-quality video transmission. To optimize cost and reduce network load, it is essential to minimize bandwidth usage while maintaining high-quality video. In response to this need, we present a novel dataset consisting of four e-learning scenarios. We encoded this dataset using various resolutions, bit rates, and encoder presets, and evaluated it in terms of encoding time, and quality using full-reference objective quality metrics such as MSE, PSNR, and SSIM. After experimenting with more than 1400 videos and configurations of encoders and codecs, we found out that it is possible to transmit videos in exceptional quality at bitrates as low as 5 Mbps for e-learning scenarios. We also present detailed results about correlation between file size, quality and encoding time to make optimizations for specific bandwidth, target quality or encoding speed.
Machine Learning Architectures to Classify Activities of Daily Living and Fall Types From Wearable Accelerometer Data

This study compares different machine learning (ML) approaches to classify motion-based activities of daily living based on accelerometer measurements, focusing on identifying different types of falls. Falls are a significant cause of injuries and deaths in older adults, emphasizing the need for real-time fall detection and alert systems. ML algorithms have shown high accuracy in detecting falls in experimental settings, but their performance in real-world scenarios still needs to be studied. Two publicly available datasets, collected from healthy subjects with smartphone accelerometers, were used for evaluation. Different ML classifiers (Support Vector Machine, Random Forest, CatBoost, and a meta-algorithm) were tested using raw accelerometer data and selected features in the time and frequency domains. Results demonstrated that CatBoost and Random Forest outperformed Support Vector Machine in both datasets when using a carefully chosen set of features instead of the raw data as input. CatBoost, although accurate, showed higher computational costs, making Random Forest a more practical choice for real-world applications. The meta-ML system did not provide a significant advantage over individual algorithms. This research contributes insights into feature selection and computational efficiency in accelerometer data classification. It provides evidence-based recommendations for practitioners working with activities of daily living classification and fall detection, aiming to enhance the use of ML in real-world scenarios and improve the quality of life for individuals requiring monitoring and fall prevention.
An Improved Multi-objective Path Planning Algorithm and its Application to Tennis Ball Collection Robots

The tennis collection robot can autonomously collect scattered tennis balls on the court, effectively reducing the workload of athletes and improving training efficiency. It has great application value in the field of sports. In this paper, we propose a multi-objective path planning scheme based on the improved A * and ACO (Ant Colony) algorithms for the ball-picking path planning problem of the tennis collecting robot. By adding a dynamic weight to the heuristic function of A *, the running rate of the algorithm is improved, and the multi-objective solution space with obstacle avoidance is obtained. On the basis of this solution space, the sequence of multi-objective traversals with fixed start and end points is solved using the improved ACO algorithm. The multi-objective ball pickup path is determined. In addition, this paper realizes the recognition and localization of tennis targets based on binocular camera and Yolov5s target detection algorithm. And using PID fixed-point navigation and visual servo strategy, the tennis ball pickup task was accomplished. Through experimental verification, the scheme proposed in this paper is robust and scalable. The tennis ball collection robot can work autonomously and collect tennis balls continuously and efficiently.
Promoting the creations of Bessarabian composers within the Romanian music festival

The purpose of this article is to review the most important events within the Romanian Music Festival (FMR) in which creations of composers from the Republic of Moldova were included. At the same time, it is aimed at highlighting the importance of promoting the Moldovan interpretative art in the Romanian space, also recorded in the chronicles that appeared after the musical events, which are proof of the interest of both Romanian musicologists and the Iași public.
On Implicit Arguments

The main objective of this article is to expound the idiosyncratic distribution of implicit arguments in the V+NP1+NP2 frame in pursuit of uncovering their seemingly unpredictable syntactic patterns. By discussing disadvantages of the syntactic analysis where implicit arguments are treated as entailed semantic arguments via some functional heads, an alternative proposal is suggested in which verbs in question are in fact not ditransitive but transitive verbs, which provides a systematic account for implicit arguments without resorting to functional heads. It may also serve as additional empirical evidence for the structural Case regularization.