Reviewerly/exHarmony huggingface dataset:
Confinement, an e-learning booster

The confinement has been one of the measures adopted to mitigate the effects of Covid-19 with the greatest effect on society, such as changes in the consumption of content e-learning due to their need to acquire new knowledge. The objective is to establish causal links between periods of confinement and the growth of consumption of e-learning resources. Data on the use of a e-learning channel have been taken and Bayesian Network have been used as a methodological instrument. The results confirm this causal relationship. It shows lines of cause-effect research that could improve e-learning content attending on the user behavior.
PELATIHAN READING SKILL DALAM PENULISAN ARTIKEL ILMIAH BERSAMA PERSEKUTUAN PELAJAR RIRING-RUMASOAL AMBON

Reading Skill as a basic reading ability for students and a tool for students to find out the meaning in writing scientific articles. The faster the student's reading ability, the greater the opportunity to understand what is read. Community Service through training in reading skills to the Riring-Rumasalah Ambonese Student Association (PRRA) which is a combination of students from Riring Village and Rumassalah Village, West Seram Regency, Maluku Province to add insight, improve thinking skills, create imagination space, increase level literacy, and improve the ability to write scientific articles. Service activities are carried out with a mentoring approach per group and are going well. need more intense and periodic education to improve the reading ability of PRRA students which is very much needed in writing scientific articles
PEMBERDAYAAN MASYARAKAT MELALUI EDUKASI LITERASI KEUANGAN KELUARGA DI DESA WAKAL KABUPATEN MALUKU TENGAH

The implementation of this community service aims to provide education on family financial literacy. This activity was carried out in Wakal Village, Leihitu District, Central Maluku, on Saturday, June 4, 2022, at 10.00 WIT. The implementation is in collaboration with students of pattimura university real work lectures placed in the village. This community empowerment event was attended by housewives and the public of Wakal Village, totaling 20 people. This activity received a good response from participants because this family financial literacy education has only been carried out in the village and it is hoped that activities like this can continue
PELATIHAN WRITING SKILL DALAM PENULISAN ARTIKEL ILMIAH BERSAMA PERSEKUTUAN PELAJAR RIRING-RUMAHSOAL AMBON (PRRA)

Writing scientific papers is considered an important skill to be mastered by students. This relates to the writing of scientific papers as part of the tridharma of higher education. On the other hand, writing scientific papers can stimulate the growth of critical, analytical, and new ideas. However, many students complain that they lack ideas and can't find anything interesting to write about. In fact, many of them have to extend their study period because they have not finished their thesis. This is all constrained by the low ability of writing scientific papers among students. Therefore, the community service that the author does is training in writing skills (writing skills) in writing scientific papers at the Riring-Rumasalah Ambonese Student Association (PRRA). This training is carried out with a classical training pattern and focus group discussions in small groups. The results of this training show that the students' ability to write scientific articles is quite low, so they need further assistance
DRHDR: A Dual branch Residual Network for Multi-Bracket High Dynamic Range Imaging

We introduce DRHDR, a Dual branch Residual Convolutional Neural Network for Multi-Bracket HDR Imaging. To address the challenges of fusing multiple brackets from dynamic scenes, we propose an efficient dual branch network that operates on two different resolutions. The full resolution branch uses a Deformable Convolutional Block to align features and retain high-frequency details. A low resolution branch with a Spatial Attention Block aims to attend wanted areas from the non-reference brackets, and suppress displaced features that could incur on ghosting artifacts. By using a dual branch approach we are able to achieve high quality results while constraining the computational resources required to estimate the HDR results.
Contrastive Regularization for Semi-Supervised Learning

Consistency regularization on label predictions becomes a fundamental technique in semi-supervised learning, but it still requires a large number of training iterations for high performance. In this study, we analyze that the consistency regularization restricts the propagation of labeling information due to the exclusion of samples with unconfident pseudo-labels in the model updates. Then, we propose contrastive regularization to improve both efficiency and accuracy of the consistency regularization by well-clustered features of unlabeled data. In specific, after strongly augmented samples are assigned to clusters by their pseudo-labels, our contrastive regularization updates the model so that the features with confident pseudo-labels aggregate the features in the same cluster, while pushing away features in different clusters. As a result, the information of confident pseudo-labels can be effectively propagated into more unlabeled samples during training by the well-clustered features. On benchmarks of semi-supervised learning tasks, our contrastive regularization improves the previous consistency-based methods and achieves state-of-the-art results, especially with fewer training iterations. Our method also shows robust performance on open-set semi-supervised learning where unlabeled data includes out-of-distribution samples.
A Depth Chronicle of General English Learning at Non-English Major Students on Joyful Communication Activities

Selecting joyful communication activities in English learning is indispensably essential. Undoubtedly, the students prefer joyful communication activities regardless the activities use assisted technology or not. Hence, this study sought to explore joyful communication activities based on EFL students' perceptions. It also aims to elicit students' attitudes toward technology-assisted and non-assisted communication activities. This study employed a mix-methods approach to obtain quantitative and qualitative data on 126 students from various non-English departments at a state university in Indonesia. Distributing the questionnaires was employed to obtain the quantitative data. Meanwhile, the qualitative data was obtained through semi-structured interviews. The findings show that three kinds of activities are recognized as the most joyful communication activities, and 12 are the medium of joyful communication activities. Furthermore, the other 16 activities are at a low position (not recommended). Regarding technology-assisted and non-assisted language learning, the student's attitude shows that they prefer to enjoy technology-non-assisted learning activities over technology-assisted activities. However, several activities using technology-assisted learning still gain students' attraction. The study suggests that lecturers should implement recognized joyful communication activities based on students' preferences for enhancing their interest in communication skill mastery.
Tackling and Handling Students’ Grammar Mastery on Passive Voices in A Higher Education: Quizizz Application Power

This research aimed to boost the grammar mastery of 24 students, particularly Passive voices using the Quizizz application and to discover their reactions to the usage of that platform for learning and assessing Passive Voices at a Private University in Blitar. This research used a classroom action research design with the following procedures: planning, acting, observing and evaluating, and reflecting. The research results revealed that the usage of the Quizizz application increased the mastery of passive voices of 24 students from 54.75 in the Pre-action Test to 87.25 on the post-action test. Furthermore, the respondents responded positively toward the usage of the Quizizz platform to learn and assess Passive Voices. Referring to the findings, we can sum up that using the Quizizz Application in Passive Voice learning is extremely beneficial in improving the students' learning outcomes since the students can learn passive voice material such as they are playing games anywhere and anytime. Therefore, the researchers suggest that teachers or lecturers may apply this application to their classrooms to make fun and enjoyable learning for the students.
Classroom Management In EFL For Young Learners at SDIT Syahiral 'Ilmi : The Strategies And Challenges

This study aims to examine classroom management in EFL for young students, especially about strategies and challenges. This research uses qualitative methods with case study design and data collection techniques using semi-structured interviews and observation. The participants of this study were 2 English teachers who teach at SDIT Syahiral Ilmi and were selected using a purposive sampling technique where the participants involved were English teachers who taught as homeroom teachers. The findings of this study are that the teacher uses seating arrangements based on student qualifications and uses a rolling system, the teacher tries to maximize the lesson plan, the teacher corrects the students depending on the student's condition and based on the student's pronouncement, the teacher also uses storytelling strategies and by provoking students' curiosity, class rules read and agreed at the beginning of the semester. This study also found several challenges for teachers in classroom management including; there are some children who are hyper active in class, parents are dishonest to the teacher, discipline the class, make students focus, then there are some children who are inclusive.
Software Framework Of An All-In-One Transpiler For Development Of WORA Applicatons

Everyone likes convenience, no one likes to go through the stress of doing or getting things through a complex means. One of the top reason why PHP and JavaScript have stood out to be the most popular and mostly used programming languages is their ability to run on a wide variety of platforms/devices (arguably all). This can't be said for many other programming languages. Programmers are faced with the tasks of keeping up with high demand of developing software for variety of technologies which runs with different kinds of programming languages. This work deals with the translation of program from one high level language to another high level language. This technique could be also be referred to as source-to-source translation. This has been shown to be an effective aid to programming in so many cases. Also it has helped in attending to major challenges, arising from code maintenance (update, debugging, and reuse etc.). The tools and techniques used in the work were; OOAD (Object Oriented Analysis and Design) diagram (Example, UML diagram), Incremental development model, JavaScript, JQuery, HTML, CSS, web browser, Xampp server. We were successful in converting from one high level language to another high level language. If this is fully implemented, it would save the cost and time taken in the development and releasing of newer and better versions of software among many notable reasons.
Strike Action And The Academic Performance Of Students In Benue State University, Makurdi, Nigeria

Abstract This study was conducted to assess the effects of strike action and the academic performance of students in Benue State University, Makurdi. The study adapted a descriptive design with a sample size of 400 respondents. Six research questions were raised from six purposes which leads to the formulation of three null hypotheses to guide the investigation. The instrument for data collection was the questionnaire which was crafted to suit the purpose of the study and it was administered to the undergraduate and Post-Graduate students. Data collected were analyzed using simple percentages and frequencies as well as mean and standard deviation in answering research questions. χ 2 -test was used to test null hypotheses 1, 2 and 3 at 0.05 alpha level of significance. Findings showed that majority of respondents agreed with all the items with regards to students’ perception about strike action carried out by ASUU, strike actions influence students’ CGPA as well as overall academic performance of the students, there is significance relationship between students reading habits and academic activities due to ASUU strike among other influences. Based on the findings of the study, it was established that Government education polices and the associated inactions and the strike embarked upon by members of the Academic Staff Union of Universities (ASUU) have contributed to the poor academic performance of the university students in Nigeria. It was recommended that the avoidable conflict between the government and ASUU must not be allowed to jeopardize the academics and future of Nigerian students, Education in Nigeria must be given its pride of place; the government must strive hard to meet the United Nation’s minimum standard. Nigerian Universities cannot be locked up permanently and government must take moves that will nip this problem of strike permanently into the bud so as to create a conducive learning environment for our students.
Unsupervised Monocular Depth Estimation in Highly Complex Environments

With the development of computational intelligence algorithms, unsupervised monocular depth and pose estimation framework, which is driven by warped photometric consistency, has shown great performance in the daytime scenario. While in some challenging environments, like night and rainy night, the essential photometric consistency hypothesis is untenable because of the complex lighting and reflection, so that the above unsupervised framework cannot be directly applied to these complex scenarios. In this paper, we investigate the problem of unsupervised monocular depth estimation in highly complex scenarios and address this challenging problem by adopting an image transfer-based domain adaptation framework. We adapt the depth model trained on day-time scenarios to be applicable to night-time scenarios, and constraints on both feature space and output space promote the framework to learn the key features for depth decoding. Meanwhile, we further tackle the effects of unstable image transfer quality on domain adaptation, and an image adaptation approach is proposed to evaluate the quality of transferred images and re-weight the corresponding losses, so as to improve the performance of the adapted depth model. Extensive experiments show the effectiveness of the proposed unsupervised framework in estimating the dense depth map from highly complex images.
Environmental Monitoring from Space &amp; Geoinformation through the Excelsior H2020 Teaming Project

The "EXCELSIOR" H2020 Widespread Teaming Phase 2 Project titled ERATOSTHENES: EXcellence Research Centre for Earth SurveiLlance and Space-Based MonItoring Of the EnviRonment is funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 857510 for a 7-year project period to establish a Centre of Excellence in Cyprus. The Government of the Republic of Cyprus is providing additional resources to support the establishment of the ERATOSTHENES Centre of Excellence (ECoE). The ECoE seeks to fill the gap by carrying out spaceborne Earth Observation (EO) activities in the Eastern Mediterranean and becoming a regional key player in the Earth Observation sector. The ECoE as a Digital Innovation Hub adopts a two-axis model, where the horizontal axis consists of three Thematic Clusters for sustained excellence in research of the ECoE in the domains of Atmosphere and Climate, Resilient Society and Big Earth Data Analytics, while the vertical axis consists of four functional areas: Infrastructure, Research, Education, and Entrepreneurship. This paper presents existing state of the art research examples within the Centre that deals with the integration of earth observation and geoinformation for monitoring systematically the environment in the areas of Agriculture monitoring, Atmospheric monitoring and Disaster risk reduction in terms of earthquakes and landslides, fires and floods.
Meteorological Data Science: exploiting causality discovery in time-series for knowledge discovery and improved forecasting

Climate change and its impact on everyday life still remains one of the greatest challenge of our era. The complex nature of climate data addresses the use of data science techniques to provide predictive analytics to the task at hand. While most existing approaches exploit correlation between observations and features to improve forecasting, the present work deals with causality, a principle that enhances robustness and provides better insight to domain experts. More specifically, a novel framework for causality discovery is proposed, based on statistical (i.e. Granger causality tests) as well as on non-linear state space reconstruction algorithms (i.e. Convergent Cross Mapping, a very effective algorithm in dynamic systems, such as the task at hand) in order to find the causal relations between meteorological time series. Furthermore, the framework also supports methods for graph analysis, thus providing informative visualizations on the influential levels of causality. Experiment results on a dataset of real observations from different cities of Greece, obtained through crawling of Internet sites of Davis weather stations demonstrate the ability to model and visualize the relations of the meteorological parameters amongst the cities. Moreover, by utilizing such causal inference knowledge, the forecasting performance for each city is significantly improved, since only relevant and informative features were taken into consideration
Tracking the object analysis movement in position data map in the Surveillance of Data object

Abstract Analysis of object tracking in the movement of order position with a sequence object that coordinate the mapped function, in order to position the object sequence that arrange the values in the trained dataset. Order Value in the coordinate function map in the position order value made in the dataset to the arranging object, the value render the movement of one positional order into the sequence of other object position. Priority Order in the functional variable that range the order sequence movement that incurs the evolution position in the trained dataset, order in the value sequence that position the coordinate map with the trained dataset. Mapping order value in the position sequence that prioritize the value position of gyration with the order movement that position the value in the priority sequence in the movement from the order position. In the Existing System pre-trained order classifier that can be used to detect objects such as sapling, registration mark, phizog, crevice aperture In the Proposed method to attain the huge computational power, in order to made in the evaluation of computationally feasible, it incurs the focus in the object movement tracking sequence in the surveillance order
AxeLatoon — Let's Build an Accelerator at School!

High Energy Accelerator Research Organization (KEK) launched an education project for the fabrication of an accelerator named "AxeLatoon" in 2020 together with the National Institute of Technology (KOSEN). This project aims to improve engineering skills of students and foster the next generation of accelerator researchers by providing hands-on training in the field of accelerator science. In the first year, we collaborated with the NIT (KOSEN), Ibaraki College to build an accelerator. Students took the initiative in this extracurricular activity and challenged building an accelerator. From 2021, we expanded this project to other prefectures and four schools are now participating. The design and fabrication of a small cyclotron accelerator is currently underway. Despite the restrictions on activities and the limited mobility of people due to the novel coronavirus pandemic, the project continues to educate students about basic technologies and accelerators. We are holding seminars a few times a month utilizing online communication tools. In this report, we would like to share the status of AxeLatoon's activities based on the actual production of students at KOSEN and deepen the discussion on accelerator outreach programs.
ML/DL/HPC Ecosystem of the HybriLIT Heterogeneous Platform (MLIT JINR): New Opportunities for Applied Research

The work presents the possibilities for using the ML/DL/HPC ecosystem deployed on the HybriLIT Heterogeneous Platform (Meshcheryakov Laboratory of Information Technologies JINR) on top of JupyterHub, which provides opportunities for solving tasks not only in the field of machine learning and deep learning, but also for the convenient organization of calculations and scientific visualization. The ecosystem allows one to develop and implement program modules in Python, as well as to carry out methodical computations. The relevance of deploying such an environment is primarily associated with the great demand for software modules that are provided to a group of researchers or the scientific community, when all stages of the study can be reproduced; the code has been modified and used by the scientific community. Using the example of solving a specific problem to study the dynamics of magnetization in a Phi-0 Josephson Junction (Superconductor-Ferromagnet-Superconductor structure), a methodology for developing software modules is presented; it enables not only to carry out calculations, but also to visualize the results of the study and accompany them with the necessary formulas and explanations. The possibility of parallel implementation of the algorithm for performing computations for various values of parameters of the model based on the Joblib Python library is shown, and the results of computational experiments demonstrating the efficiency of parallel data processing are presented.
USING VIDEO ON YOUTUBE TO IMPROVE STUDENTS’ GRAMMAR ABILITY

The rapid development of technology has had an impact on the field of education. In this case, an educator must be able to be more creative and innovative to build and stimulate students' interest to learn in the classroom while teaching learning process. One of the positive things from the impact of technological developments to support the teaching and learning process is the use of technology-based learning media such as making interesting videos and uploading them to YouTube. YouTube videos can be repeated and can be accessed anywhere if the device and internet network support. YouTube videos were used in this study as a learning media to improve students’ grammar ability. The sudents in this study are the first semester majoring accounting at Institut Teknologi dan Bisnis Indonesia. The total number of students in this Classroom Action Research (CAR) is 30 students. After taking two cycles of action, it can be concluded that the use of videos that are made as attractive as possible and uploaded to YouTube as a learning media to improve students' grammar ability is effective in the teaching and learning process, besides that YouTube is also universal, can be viewed repeatedly, and can enhance the creativity of an educator.