Reviewerly/exHarmony huggingface dataset:
Kemampuan Literasi Digital Orang Tua Dalam Mengasuh Anak: Studi Kasus Di Desa Curug, Gunung Sindur, Bogor

This research aims to find out parents' abilities in Islamic parenting, their digital literacy skills, and whether there is an influence of Islamic parenting skills on parents' digital parenting skills. This research was carried out with a quantitative approach using simple regression analysis. Respondents in this study totaled 58 people. The sampling technique used was a purposive sampling technique where the respondents selected were parents who met 2 main criteria. First, parents already have children who are at least 3 years old and above. Second, parents have the ability to use cell phones or other gadgets to access the internet. The research results show that parents' abilities in Islamic parenting are very high, reaching a score of 3.34. Likewise, in terms of digital parenting, parents' abilities are also quite high because they reach a score of 3.1. Then regarding the question of whether there is an influence of Islamic parenting skills on digital parenting, the answer is that there is a very significant influence, namely 0.81344502 from the results of using the Pearson product-moment formula.
Children's Literacy Activities as a Realization of the School Library Revitalization Program at SDN 1 Moyoketen, Tulungagung Regency

Currently, the use of devices in children is increasing, accompanied by a decrease in literacy rates. From the results of the study, the level of literacy in children is quite low. To increase interest in reading in children not only requires the role of parents, but the place where they go to school also takes an important role in improving children's literacy. Low literacy of children can be overcome by carrying out various activities regarding literacy itself. Another alternative that can be done is to hold a literacy program in the school library. It aims to assist children in improving and growing their reading literacy as well as the realization of revitalization. This activity took place from July to August at SDN 1 Moyoketen. With the literacy program and library revitalization, it is hoped that it can make students more interested in visiting the library and reading the collections contained in the school library
Evaluasi Desain User Interface Berdasarkan User Experience Pada Aplikasi Perpustakaan Digital Isleman

Research related to evaluation of user interface design based on user experience in Isleman Digital Library Application aims to evaluate the user interface design of Isleman digital library application based on user experience. A qualitative approach is used as a research method, the collection of material through interviews, observation and analysis of related documentation. The results showed that the user interface design of the Isleman digital library application received positive responses from users. They find the design intuitive, easy to use, and present information clearly. Users also appreciate the program's clean layout and easy navigation, which allows them to easily find and access the library resources they need. Features such as efficient search, responsive display, and integration with other library management systems have also received positive reviews from users. These features are designed to improve usability and help users find and manage library materials more efficiently. However, some users provided feedback on minor improvements to the UI design, such as improved icon appearance and text clarity in some parts of the app. Based on the results of this study, several corrective steps are suggested to improve the user experience of the Isleman digital library application. These steps include visual enhancements, clarifying text and instructions, and changing the layout to make it more responsive and user-friendly. This research makes a major contribution to understanding the user's perspective on the user interface design of Isleman's digital library and provides recommendations for improvements that can be applied to improve the overall user experience.
Analisis Kebutuhan Informasi Tenaga Pendidik Pada Anak Penyandang Disleksia Di Sekolah Luar Biasa Amal Mulia Yayasan Dharma Bhakti Kesejahteraan Sosial Kota Bengkulu

Educators have a very important role to improve the ability of students in the teaching and learning process. The tasks and roles of educators can be achieved well if educators have qualified information needs. This research focuses on the information needs of educators in educating dyslexic students. The purpose of this study was to determine the information needs of educators in dyslexic children at SLB Amal Mulia Yayasan Dharma Bhakti Social Welfare Bengkulu City in the learning process. The qualitative method is descriptive and has 3 information as data sources, observation interview techniques and documentation. The results showed in terms of psychological needs, affective needs, cognitive needs where all aspects of educators have implemented well, but there is still a need for further development in accessing information needs. The information needs of SLB Amal Mulia educators, Yayasan Dharma Bhakti Social Welfare Bengkulu City, have good enough knowledge in educating dyslexic students even though they do not have basic skills as special educators. This can be seen from the ability of educators to access information needs, evaluate information needs and use information as well as possible to educate dyslexic students in the teaching and learning process to run effectively and efficiently.
Analisis Kompetensi Pustakawan dalam Mendukung Layanan Perpustakaan (Studi Kasus di Perpustakaan UIN Sunan Gunung Djati Bandung)

One of the determining factors in efforts to improve the quality of service in university libraries is to increase the competence of librarians. The digital era has changed the role of the library which has an impact on service changes. Accordingly, this study analyzes the competency of librarians in supporting library services at the Library of Islamic State of Sunan Gunung Djati Bandung using American Library Association (ALA) standards. The research approach uses descriptive qualitative with a case study model where researchers observe and examine documents and gather information by interviewing librarians, heads of libraries, heads of administration and staffing bureaus, and users consisting of lecturers and student. The results of the analysis show that the competence of librarians is still limited to managing printed collections. As for digital services, only 0.26% of the total number of librarians manage it so competencies related to digital library services need to be improved and developed.
The Role of Artificial Intelligence-Based Technology with ChatGPT as an Educational Learning Media Innovation in Indonesia

ChatGPT with OpenAI is an artificial intelligence-based machine technology that is trained to imitate human conversation using NLP (Natural Language Processing) technology. ChatGPT can be used to produce quite scientific writing with good and effective formulation techniques. With the help of OpenAI technology, ChatGpt can help innovate in creating learning media and learning tools such as creating RPS (Semester Learning Plans) and writing textbooks for teaching staff, especially at the tertiary level. The aim of this research is to clarify the role of artificial intelligence in the world of education and this research method uses qualitative methods. The results of experiments carried out by researchers using ChatGPT produced + 693 words of writing, this number can still be developed further. The time speed only requires + 5-7 minutes to complete this experiment and includes time to document the processing results from ChatGPT.In conclusion, ChatGPT is useful, namely teaching, research and community service. So the presence of ChatGPT as a tool in creating scientific works, learning tools (RPS) and textbooks. Another benefit of ChatGpt, especially in developing the competencies (skills) of teaching staff (lecturers), can help carry out the Tri Dharma of Higher Education technology opens up opportunities to utilize this AI chatbot for education in Indonesia
From The Internet of Things (IoT) to The Internet of Behaviors (IoB) for Data Analysis

The Internet of Behaviors (IoB), a relatively new research and development area, can be considered an ecosystem that blends technology, advanced data analysis, edge analytics, and behavioral science, and aims to aggregate, analyze and comprehend, from the standpoint of human psychology, the users’ data gathered from IoT devices and online platforms. Then, utilize this comprehension to alter or influence human behavior. In this paper, we provide an up-to-date literature review and explain the $I o B$, its primary characteristics, and its connection to IoT and the DKIW pyramid. Then, we focus on IoB key-enablers technologies, summarize the main IoB application fields and domains, and describe the challenges to be addressed by the IoB ecosystem.
Machine Learning based Identity and Access Management Systems (ML I&amp;AM): a Taxonomy

Identity and access management (I&AM) systems are at the heart of every organization that is conscious of its own operations. Major corporations and software entities center their principles around the meticulous administration of identities within their scope. Machine learning (ML) techniques can be effectively utilized to improve and strengthen I&AM systems by enhancing security, user experience, and overall system efficiency. In this regard, we introduce a taxonomy of ML-driven I&AM, our objective is to provide a classification of the state of the art approaches applied within the realm of identity and access management systems.
Analytical study of Virtual reality in Moroccan higher education

The Virtual reality (VR) experience immerses users in an interactive digital environment similar to the real world. In the context of education, virtual reality can represent an active learning tool which could improve learning outcomes for students by involving their visualization and their interactivity with virtual dynamic and complex systems. Nowadays this technology become widely employed in many higher education programs all over the world.This paper examines the use of VR in Moroccan higher education context. The study begins with stating the current situation of VR in education in general, and then in Moroccan higher education. The results of this state of the art are gathered with an empirical analysis of VR integration into some post-secondary institutions and schools’ pedagogy and curricula. These results helped then to conduct a SWOT analysis of virtual reality technologies in Moroccan higher education environment. A particular case study of mechanical engineering skills is highlighted.Findings show that Morocco has significant potential to effectively adopt this technology, contingent upon addressing the current inconveniences and constraints. Through the successful navigation of these challenges, the nation has the potential to leverage the advantages of virtual reality technology, thereby transforming its educational domain. This study highlights the importance of strategic planning and investment in order to effectively harness the benefits of virtual reality in increasing educational experiences and equipping students for future endeavors.
Gesture Recognition and Computer Vision:A Bibliometric Analysis

Recently, human-computer interaction (HCI) has been developed significantly. The recent technologies and techniques are used to improve how humans interact with machines. Gesture recognition is one such development, which allows for more natural and effective interaction between humans and computers. This work is a bibliometric analysis that aims to provide an overview of research trends in the field of gesture recognition. To achieve this goal, we conducted a systematic search of the Scopus database, selecting articles published between 2012 and 2022. A total of1,703 articles were analyzed. This analysis focused on several aspects, including the number of publications, the most prolific authors, and the top journals in the field. The findings of this study shed light on the research trends and priorities in gesture recognition.
Anomaly Detection in PV Modules: A Comparative Study of DBSCAN, k-means, Isolation Forest, and LOF

The increasing adoption of photovoltaic (PV) modules for renewable energy generation highlights the importance of maintaining their performance and efficiency. Anomalies in PV modules can lead to energy losses and reduced system reliability. Classical approaches for detecting PV module anomalies include current-voltage (IV) curve analysis, visual inspection, infrared thermography, and electroluminescence imaging. However, these methods often require employees, manual intervention, and may lack scalability and accuracy.In this study, we explore unsupervised machine learning techniques for detecting anomalies in PV modules using data from a PV plant, aiming to develop more efficient and accurate solutions compared to classical approaches. We evaluate four unsupervised machine learning algorithms—Isolation Forest, Local Outlier Factor (LOF), K-Means and DBSCAN, and compare their effectiveness based on metrics such as accuracy, precision, recall, and F1 score.Our findings reveal that the K-Means and DBSCAN algorithms, when properly tuned, demonstrate superior performance in detecting anomalies, while other algorithms show promise with further optimization. This study provides insights into the potential of unsupervised machine learning algorithms as an alternative to classical approaches for anomaly detection in PV modules, contributing to the development of efficient, accurate, and scalable anomaly detection systems in the solar energy sector and enhancing PV system performance and reliability.
Blockchain-Enabled Edge Computing and Sensor Integration for IoT-based Smart Grid Systems – Implementation and Energy Management: Morocco Case Study

The advent of IoT-driven smart grid systems heralds new possibilities for refined energy management, with the potential to decrease costs and bolster sustainability. Nevertheless, challenges persist in optimizing energy usage and enhancing energy efficiency within these systems. Historically, the reliance on centralized systems or traditional communication methods has led to constraints such as limited scalability, excessive latency, and vulnerability to cyberattacks. This paper presents an innovative solution for optimized energy production and distribution, leveraging the capabilities of blockchain and edge computing technologies. The proposal utilizes real-time data procured through smart meters, aiming to achieve effective, secure, and sustainable resource utilization while simultaneously minimizing energy wastage. These smart meters collect energy consumption and production data from both residential and commercial entities, securely storing this data on a blockchain platform. Data processing is executed at the edge of the network, closer to its generation source, to curb latency and boost reliability. This paper also provides a preliminary cost analysis of implementing the proposed system in a Moroccan.
Comparative Analysis of Datasets for Response-based Knowledge Distillation in Image Classification

This paper presents a comparative analysis of different datasets’ influence on the effectiveness of response-based knowledge distillation in image classification. Through a series of experiments and evaluations, we explore the impact of dataset choice on the performance and transferability of distilled models. Our findings provide insights into optimizing dataset selection for response-based knowledge distillation, a critical aspect of model compression and transfer learning.
Incorporating a cryptographic-based Blockchain technology to revolutionize degree automation

The paper aims to analyze the new methods of securely digitizing university diplomas and certificates. Traditionally, the essential role of university diplomas and certificates has been to validate the study process and provide proof of knowledge. However, the manual method of handling these documents is limited to a trusted third party, i.e., the university. This limitation has led to the birth of new studies that allow for the automatic management of university certificates and diplomas without recourse to a trusted third party. The new method of digitizing diplomas and certificates involves using blockchain technology, which provides a sustainable, better secured, and valued degree against other countries. To analyze the feasibility of these new methods in the Moroccan context, a qualitative study was conducted at the level of work related to certificates and university diplomas signed automatically, for this, we will present a model that combines the solutions found. Overall, the paper aims to explore the potential benefits of digitizing university diplomas and certificates, such as improved security, accessibility, and portability.
Measuring the effectiveness of the Augmented Reality Technology on Muscular Rehabilitation endurance and coordination

Augmented reality-based rehabilitation programs have great advantages in terms of extending therapy sessions and promoting engagement. This study confirms whether the augmented reality (AR)-based exercise program is effective in improving basic physical strength and as effective as existing traditional exercise. Methods: Twenty-eight adults who voluntarily participated in this study were randomly distributed between the two groups and intervene by AR and physical therapist for four weeks each. Paired t-test was used to confirm the effect of intervention within the group, and dependent t-test was used to compare the two groups. Both groups improved muscle endurance, balance, flexibility, and coordination, and there was no statistically significant difference in handgrip and cardiopulmonary endurance. In the comparison between groups, there was a significant difference only in the right handgrip pre and post. AR-based exercise programs have been as effective as conventional exercise programs and can be selected according to individual conditions.
Study of Solar Energy Gains in Algeria: Comparison of Monthly versus Annual Inclination

The theoretical findings from this study reveal that the gain in extraterrestrial radiation between optimal monthly calibration and fixed annual calibration for 10 selected towns in Algeria is approximately 10%. Furthermore, experimental results obtained during a demonstration conducted in 2010 at the Renewable Energy Research Unit in the Saharan Medium (URER/Ms) headquarters in Adrar town demonstrate that the actual solar energy supply on the south-facing plane closely matches the optimal extraterrestrial contribution. The deviation is estimated to be only about 9% from a fixed yearly inclination throughout the year. These results serve as a fundamental reference for optimizing solar systems to achieve the desired performance levels during the design phase.
Experimental Validation of PV Module Modeling Based on Interpolation Approach in Outdoor Operating Conditions in the Southern Algerian Desert Regions

Modelling and extracting the characteristics of a photovoltaic (PV) panel are crucial aspects in researching and advancing PV systems. PV cell modeling needs to take into account the actual irradiance spectrum data for each location under practical working conditions. Unfortunately, the nonlinear nature of the panel model makes it challenging to solve with analytical methods. In this study, a mathematically simple approach called bilinear interpolation was presented and used to model and simulate the I-V curves of PV modules in order to translate the I-V curves under all given radiation and temperature conditions. Under the climatic circumstances of the Algerian desert, the modeling results by bilinear interpolation were examined and compared with the experimental results. Whereas, this modeling method was applied to three different module technologies: mono-crystalline (ET Solar-75W), polycrystalline (PHOTOWATT PW500), and thin film (QS Solar 60W). The results of the bilinear interpolation approach validation were very satisfactory. Furthermore, the method enabled us to obtain updated STC characteristics values after many years of PV panel use; as a result, the studied approach was one of the best methods for studying photovoltaic panel degradation.
Effective Spline-GMPPT Approach Performance for Photovoltaic Systems under Uniform Irradiance and Partial Shading Conditions

In the literature, there are several criteria techniques classified to achieve the point of maximum power tracking (MPPT) in photovoltaic (PV) power systems, such as accuracy, speed, and simplicity. These criteria are often trade-offs; in this case, the higher accuracy generally achieved at the expense of two other criteria: speed and simplicity.This contribution proposes a new technique based on the Spline-Global-MPPT approach to provide its reliability in multiple criteria as an accurate, fast, and simple technique to find the MPP of PV power generation systems under two cases, such as uniform irradiance and partial shading conditions (PSCs), in the total distorted characteristics of the PV string. A cubic spline interpolation approach has proposed in this method, which defines from a few simple points an approximate function.To localize the GMPP under standard (uniform) irradiance conditions, there are a huge number of interpolation-based approaches proposed in the literature. Unfortunately, this interpolation approach became incapable of detecting the point of the global maximum power (GMPP) under PSCs. The MPP of the system predicted by this new Spline-GMPPT method using a limited sample set of current and voltage, and it maintains this position as long as the external conditions stay unchanged. In the last part, the simulation results prove the reliability and robustness of the proposed approach.
Automated Text Selection for Raw Data Annotation

The escalating volume of user-generated web content urges the need for advancements in automated text processing. The performance of state-of-the-art machine learning and deep learning techniques is significantly influenced by the quality of training data. However, real-world user-generated web content often contains excessive repetition. Such redundancy and data bloat have the potential to impede the performance of automated text analysis algorithms. Training datasets must mirror real-world complexity for optimal generalization, maintaining a balance between diversity and relevance, with minimal redundancy. Moreover, advanced techniques for natural language analysis are data-hungry; hence, substantial efforts are required to prepare a suitably large dataset. Large datasets are prepared by a group of team members, with each team member working on their own chunk of data, as it is not feasible for a single person to go through a huge amount of data alone. Therefore, automated text pruning can facilitate the selection of diverse text and enrich the meaningful vocabulary by reducing redundancy and eliminating unnecessary and irrelevant information. Hence, in this study, we propose text selection techniques based on text similarity for automated unique review selection from a large dataset. However, with large datasets, direct pairwise similarity comparison drastically increases the time complexity for similarity matching. Therefore, we adopted a cluster-based vectorized text pruning technique for similarity-based redundancy removal.