Reviewerly/exHarmony huggingface dataset:
Peningkatan kualitas pengajaran di era digital melalui pelatihan pengembangan video pembelajaran interaktif

Effective teaching in the digital era poses a major challenge in education, especially in elementary schools. This study highlights the importance of interactive learning media in enhancing teaching quality. Utilizing methods of presentation, discussion, and mentoring, this training targeted 50 elementary school teachers at SDN 39 and SDN 08 Sungai Kakap. The main focus was on creating educational videos using Microsoft PowerPoint, a software commonly used by teachers. The training content included the definition of educational videos, steps in video creation, tips for making engaging videos, and using PowerPoint for educational purposes. Pre-tests and post-tests were conducted to measure participants' understanding before and after the training. Results showed a significant improvement in understanding and skills in creating educational videos, with average pre-test scores rising from 54 to 93 in post-tests. Participants realized that PowerPoint is not only for presentations but also an effective tool for creating engaging and efficient educational videos. This research affirms that technology-based interactive learning, such as PowerPoint educational videos, enhances teachers' enthusiasm and student engagement, and supports teaching effectiveness in elementary schools. The main conclusion is that educational technology training like this is crucial for enhancing teachers' creativity and the quality of learning in the digital era.
Unveiling the Thirst: Revealing the Water Requirements of Gujrat's Thriving Crops using CROPWAT 8.0

Water plays an essential role in agriculture, serving as a primary reserve that directly impacts crop production and food security. Water conservation is critical for sustainable agriculture and the well-being of communities and ecosystems, chiefly due to the increasing global demand and rising water dearth concerns. The water needs of crops and irrigation scheduling in the district Gujrat, Pakistan, are currently missing enough information. Therefore, this study was conducted to determine the crop water requirements and establish irrigation schedules for the major crops in district Gujrat, Pakistan. The crop water requirement (CWR) and irrigation schedules were determined by CROPWAT 8.0 by using the input climate data obtained from the POWER-NASA website from 1991-2020. Other than climatic data, crops (wheat, rice, sugarcane, and maize) and soil information were added from CROPWAT 8.0 pre-existing data. The crop planting dates were estimated by Ayub Agriculture Research Institute (AARI). The gross and net crop water requirements are 624.3 mm and 491.3 mm for wheat, 1805.2 mm and 1768.3 mm for rice, 4135.1 mm and 3537.2 mm for sugarcane, and 1203.5 mm and 1051.4 mm for maize. The deployment of CROPWAT 8.0 proves to be valuable in precisely assessing crop water requirements and computing irrigation scheduling. The study's outcomes show the potential to boost food production and aid in well-organized water reserve management.
Effect of Social Practice Approach on Academic Achievement of Adult Learners in Basic Literacy

The challenge of low academic achievement among adult learners has been continuously reported in adult basic literacy. Adult literacy programs prioritize integrating basic life-related literacy, empowering learners to manage daily responsibilities independently and enhancing academic achievement. Therefore, the present study was conducted to empirically investigate the effect of the social practice approach on learners' academic achievement through pretest, protest control group design. They involved 70 learners, with 35 assigned to each experimental and control group. A worksheet (pretest/posttest) was employed for data collection. Data were analyzed by using an independent sample t-test. The findings revealed that the experimental group, exposed to the social practice approach in their literacy activities, showed improved academic achievement. The study recommended conducting learner assessments before literacy content development to align with identified social needs, offering context-based literacy training for teachers, and establishing an assessment and evaluation system that forges connections between learners' daily lives and literacy practices. Furthermore, it suggested implementing virtual and physical feedback mechanisms to gather input from adult learners to enhance adult basic literacy consistently.
In Constant Search for Affection: Untold Narratives of Juvenile Delinquents or “SUKARAP” in Davao Region

“Sukarap,” derived from “stagger,” reflects uncontrolled movements while walking. This qualitative-phenomenological study focuses on the challenges faced by Sukarap members in the Davao Region. Examining their involvement, reasons, challenges, and coping mechanisms, the research engaged 14 Sukarap members through interviews and discussions. Participants revealed experiences of painful initiation, exposure to vices, street riots, and life-threatening situations. Coping strategies included diversion, peer support, and ignoring challenges. Insights from Sukarap members highlighted belongingness, learning, and opportunities for change. In conclusion, the study emphasizes the importance of education and affection in nurturing the optimal development of delinquent juveniles seeking attention and affection outside their families. Keywords: gang, gangsterism, plight, Sukarap, stories to tell
Perceptions and attitudes of the students of Babeș-Bolyai University towards online, face-to-face, and hybrid learning during the COVID-19 pandemic

This paper presents the findings of an exploratory sociological survey conducted at Babeș-Bolyai University of Cluj-Napoca focusing on student experiences during the COVID-19 pandemic. The paper aims to investigate student experiences and attitudes toward different modes of education. Our research goals were to evaluate students’ perspectives on online, face-to-face, and hybrid teaching activities, to assess the challenges they faced, to group students into clusters based on their attitudes toward online learning and to identify those factors that shape student experiences and preferences. The study utilizes cluster analysis as a methodological approach to categorize students into three groups according to their preferences for teaching modes: (1) ‘Balancers’ (43.5%) favored a blend of online and in-person classes, (2) ‘Onliners’ or ‘screenagers’ (28.9%) preferred online courses, as opposed to (3) the adepts of face-to-face learning (27.6%). In spite of its challenges, online teaching was preferred by nearly 30% of the students, among whom those pursing their master’s degrees and young people coming from lower status families and thus already in employment were overrepresented. Their experiences and attitudes show that these students have indeed developed effective strategies for online education. In opposition to those who preferred face-to-face classes, ‘onliners’ were more likely to show satisfaction with their teachers, more likely to be better equipped for online courses and also to have passed the exams. With these results the article contributes to the scholarly and expert debate concerning the possible effects of the flexibilization of higher education upon students’ access to tertiary education. We argue that for an important segment of the students, online courses provided a valuable chance to pursue their studies which they took advantage of, showing higher levels of commitment and willingness to meet the university requirements.
Exploring Greenockite: Occurrences and Geological Setting

Greenockite, mineral containing cadmium, is of significant scientific interest owing to its remarkable properties and potential applications in the field of science. It commonly forms in hydrothermal ore deposits as a secondary mineral due to complex cadmium-sulfur interactions influenced by temperature. Typically, it replaces zinc minerals like sphalerite, depending on the abundance of cadmium and zinc in hydrothermal fluids. Solid solubility in the ZnS CdS system occurs at high temperatures, with immiscibility observed under specific conditions. Greenockite forms at relatively low temperatures (100°C to 200°C) and is influenced by factors such as oxygen fugacity, hydrogen sulfide activity, and chloride ion content. Its hexagonal zinc blende structure results in diverse crystal forms, including rods, wires, and whiskers, often adorned with bismuth drops. Experimental studies have identified factors affecting its formation, such as solid solubility, precipitation mechanisms, pH levels, and fluid composition. Its vibrant coloration, attributed to cadmium concentration, varies from pale yellow to deep orange-red. Geologically, it is present in diverse settings, including metamorphosed zinc oxide mineralization, granites, fumaroles, pegmatites, and sediment-hosted Pb-Zn deposits, with a unique occurrence in gabbroic rock at the Babbitt deposit. In India, Greenockite has been identified in the Bagada orogenic gold prospect, situated within the Paleoproterozoic Mahakoshal belt, Central Indian Tectonic Zone (CITZ). Additionally, it is found in hydrothermal deposits of Pb-Zn mines of Zawar. It is exclusively encountered within specific geological settings, primarily as a secondary product. This paper provides a comprehensive exploration of its geological occurrences, distribution, associations, and exceptions.
Enhancing English Technical Report Writing for Engineering Students through a Constructivist-Based Program Using Docear Software

This study examines the impact of a constructivist-basedprogram using Docear Software on developing technical reportwriting skills of the second-year students of the electricalengineering department at the Faculty of Engineering in Shubra,Benha University (N=45) To evaluate the participants'proficiency, the study used a technical report writing skillschecklist and a test as well as a list of electrical engineeringterminology. Additionally, the researcher developed theconstructivist-based program using Docear Software. The studyadopted the quasi-experimental design with the pre-post onegroup design. The findings of this study show statisticallysignificant difference in the technical report writing skills. Theprogram clearly had a significant impact on students' writingskills, as shown by the considerable effect size (
Error estimation for the third-order accuracy approximate solution of the Cauchy problem by the Taylor formula

A method based on the Taylor formula for the approximate solution of the Cauchy problem for the ordinary differential equation is studied. The problem of estimating the accuracy of the approximate solution generated by this method is considered, and an estimate of high accuracy is obtained for the difference of the exact and approximate solution. Here, different from the known values, an exact expression for the estimation coefficient is found.
Aircraft Recognition in Remote Sensing Images Based on Artificial Neural Networks

Computer Vision (CV) is a field of Artificial Intelligence (AI) that enables computers and systems to obtain data from images, recordings and other visual information sources. Image Recognition, a subcategory of Computer Vision, addresses a bunch of strategies for perceiving and taking apart pictures to engage the automation of a specific task. It is fit for perceiving places, people, objects and various types of parts inside an image, and reaching deductions from them by analyzing them. With these kinds of utilities it is a no-brainer that Computer Vision has its use cases in the military world. Computer Vision can be immensely useful for Intelligence, Surveillance and Reconnaissance (ISR) work. This paper provides on how Computer Vision might be used in ISR work. This paper utilises Artificial Neural Network (ANN) such as Convolutional Neural Network (CNN) and Residual Neural Network (ResNet) for demonstration purposes. In the end, the ResNet model managed to edge out the CNN model with a final validation accuracy of 90.9% compared to a validation accuracy of 86% on the CNN model. With this, Computer Vision can help enhance the efficiency of human operators in image and video data related work.
Managing Student Mobility in Cameroon’s University Ecosystem: A FORM/BCS Approach

Nowadays, student mobility cannot be avoided in Cameroon university ecosystem. This phenomenon has many causes. Certain students live with their parents who are civil servants and they have to move with them when they are sending to a different region; another situation is link to universities newly created in cities where the cost of the live is better than in the home university city and students prefer move to these new universities. Since student circuit is not the same in each university, it is difficult to find his level in the new university and which courses he has to follow in order to complete his training. This problem is crucial in Cameroon university ecosystem and we tackle it in this paper. The Feature Oriented Reuse Method with Business Component Semantics (FORM/BCS) is a software domain engineering method that has been proposed to design an adaptable architecture for systems belonging in a same business domain. In this work, we apply the FORM/BCS method to manage student mobility in Cameroon university ecosystem. The result of this work is a management model that allows once a student gets an enrolment in a new university, to transfer credit from the student home university to the host one.
Investigating privacy-preserving machine learning for healthcare data sharing through federated learning

Privacy-Preserving Machine Learning (PPML) is a pivotal paradigm in healthcare research, offering innovative solutions to the challenges of data sharing and privacy preservation. In the context of Federated Learning, this paper investigates the implementation of PPML for healthcare data sharing, focusing on the dynamic nature of data collection, sample sizes, data modalities, patient demographics, and comorbidity indices. The results reveal substantial variations in sample sizes across substudies, underscoring the need to align data collection with research objectives and available resources. The distribution of measures demonstrates a balanced approach to healthcare data modalities, ensuring data fairness and equity. The interplay between average age and sample size highlights the significance of tailored privacy-preserving strategies. The comorbidity index distribution provides insights into the health status of the studied population and aids in personalized healthcare. Additionally, the fluctuation of sample sizes over substudies emphasizes the adaptability of privacy-preserving machine learning models in diverse healthcare research scenarios. Overall, this investigation contributes to the evolving landscape of healthcare data sharing by addressing the challenges of data heterogeneity, regulatory compliance, and collaborative model development. The findings empower researchers and healthcare professionals to strike a balance between data utility and privacy preservation, ultimately advancing the field of privacy-preserving machine learning in healthcare research.
Location-specific trusted third-party authentication model for environment monitoring using internet of things and an enhancement of quality of service

In the modern digital world, the Internet of Things (IoT) is a modern and advanced technology that interconnects many immeasurable devices. The collection of wireless sensors formed the wireless sensor network. WSN nodes are battery-powered nodes with limited power and computational capability. When using loT-based wireless sensor networks, the nodes are used to communicate with the internet, where there is a need for more secure protocols. In this technological era where time factor plays a key role in everyone’s personal busy life. The need for smart and sensor appliances that work without human intervention can be a solution to some extent for the time factor. IoT is a network where physical objects, vehicles, devices, buildings and many other smart devices are electronically embedded with hardware and software with huge network connectivity. But the communication and data exchange are not that much easy to carry out, it requires a high secured protocol for authentication as well as key encryptions. Besides focusing on secured key distribution importance for enhancing various parameters are also considered which includes, EC additions, multiplications, pairing, hash-to-point operations, security performances, and energy consumption are also considered. In this paper, focuses on “LSTTP” which authenticates the nodes based on the Device Finger Print (DFP) with a Trusted Third Party and proposes the algorithm for enhancing the quality of service parameters such as Throughput, Jitter, Latency and Security.
Efficient I3D-VGG19-based architecture for human activity recognition

Systems for autonomously identifying and analyzing human activities (HAR) make use of video data captured from various devices area requires ongoing updates due to the developing technology and multidisciplinary nature of HAR. Objective of this research is to classify different activity performed by Human using various pretrained models and latest transfer learning methods. Set the hyperparameters values to get accurate classification based on different performance evaluation matrices. In this study, the VGG19 based optimized I3D architecture is proposed. The experimental findings demonstrate that use of optimized VGG19 based I3D model on the UCF-50 dataset has led to an enhancement in the performance of the Human Activity recognition system with accuracy rate of training is 98.24% and testing is 98.36%, surpassing the performance of alternative I3D model using DenseNet121 in direct comparison. This will facilitate the development of applications like Smart Environments, Elderly Care and Assistive Technologies, Healthcare and Wellness and various other domains.
Cost-based resource allocation method for efficient allocation of resources in a heterogeneous cloud environment

Cloud computing is appealing due to features like adaptability, portability, utility service and on-demand service. Cloud resource providers are a source of computing, and each provider delivers different types of resources. In an active cloud environment, timely resource allocation is more important. In order to increase the effectiveness and user-friendliness of resource allocation in the heterogeneous cloud, the paper suggests an efficient cost-based resource allocation (ECRA) method and framework. In the heterogeneous cloud, there is no centralized resource allocation manager (CRAM) to get all requested resources from a single counter. The proposed methodology for allocating resources divides them according to their cost. The paper’s framework for allocating resources consists of various parts. The Unified Heterogeneous Resource Allocation Manager (UHRAM) part of the framework collects and manages resources from several cloud resource providers. The resource identifier is one of the components in the framework, which is coupled to UHRAM to determine the cost of the resources. The low-cost resources are scheduled and to be in a ready state for allocation. The proposed ECRA is simulated and compared based on parameters like total computation time, response time and resource allocation percentage with existing resource allocation methods. The results prove that the proposed ECRA is efficient in allocating the resources in minimum response time and it allocates maximum resources for lower cost.
Smart Dc to DC converter for a Small Drone Based upon Deep Learning Technique

Flying a small robot like a drone needs more conservative energy, small solar cell size needs to robust efficient DC-to-DC converter. Mathematical analysis for finding the optimal duty cycle in the PWM (pulse width modulation) is presented at different supplies voltage, considering a low voltage of 8 volts for low-speed motor rotation speed and 18 volts for high speed of the rotation motor. The dc-dc converter gets the power desired from the small robotic by using a dc-dc buck-boost converter with (PID control, smart tuning different rules fuzzy logic control, and a hybrid fuzzy-PID controller as one solution to be improved the controller to be capable on process any disturbances on the inductor or the desired value of the output voltage of the dc-dc converter
FORMATION OF GEOECOLOGICAL RESEARCH COMPETENCE OF FUTURE GEOGRAPHY TEACHERS WITH THE USE OF STEAM-TECHNOLOGY IN THE STUDY OF BASIC AND PROFILE DISCIPLINES

The article explores the role of STEAM-technology in the formation of geoecological research competence of future geography teachers while they study the basic and profile disciplines. It reviews the effective methods of STEAM-technology application based on the use of remote sensing data, digital interactive maps and the findings of empirical field research in the learning process. The article provides practical examples of the outcomes derived from implementing STEAM technology. Scrutinizing the essence of STEAM technology and the aspects of integration thereof into the educational process revealed that this approach harbors substantial potential for fostering the geoecological research competence and enhancing the functional proficiency of future geography teachers, which aligns with the demands of our information-driven society in the context of revitalizing educational content. The research methods employed were chosen meticulously to comply with the research's objectives, tasks, and practical significance. In order to tackle the research tasks effectively, we applied a combination of observational, analytical, evaluative, design, and experimental research methods. The core principles and conclusions expounded in the article can be applied in practice when incorporating STEAM-technology into geography education within general secondary schools and higher education institutions to foster students' geoecological research competence and improve their functional literacy. According to the authors, the use of STEAM-technology promises to not only advance critical thinking and intellectual capabilities but also to lay the groundwork for creative involvement in future professional endeavors, since it necessitates the use of collaboration, communication, and collective interaction skills.
ON THE PROBLEM OF FORMATION OF FUTURE FOREIGN LANGUAGE TEACHERS’ DIGITAL COMPETENCE

The article deals with the problems and analysis of approaches to the definition of digital competence of a foreign language teacher. The relevance of the research problem stems from the need to modify the content of the professional training of a teacher of foreign languages. The research methodology involves the review and consolidation of the papers of both domestic and international scholars studious of this particular domain, enabling us to pinpoint the key concepts. In addition, the article reveals the problems of forming the digital competence of future foreign language teachers, analyzes the extent of development of this concept in the scientific pedagogical literature, determines the main mechanisms of the digital competence formation, and clarifies the components that make up the digital competence of a foreign language teacher. The article offers examples of exercises and tasks based on information and educational resources (analytical and prognostic, situational and communicative, pragmatic and updating, informational and retrieval) aimed at fostering the digital competence of a future foreign language teacher. The developed methodology and tasks were tested in the course of the experimental and practical training during the foreign language classes involving the second-year students, and validated by the experimental work results.