Reviewerly/exHarmony huggingface dataset:
Balance of traditional and innovative ingredients in the modern educational space

The purpose of the study is to highlight the perspectives of educational strategies in which the principles of innovation and traditionality are harmonized. The tasks of the article are focused around the search for theoretical-methodological and educational-practical guidelines for the correlation of innovative ideas with the traditional educational space. The research methodology is based on general scientific methods (analysis, forecasting, systematization), which provide an understanding of the foundations and features of scientific and pedagogical discourse; philosophical and scientific methods (synergy, dialectics), thanks to which awareness of the coexistence and interaction of educational elements or development strategies is formed. Elements of the novelty of scientific intelligence are focused on taking into account the cultural norms and traditions of the community in which innovative transformations are implemented in the educational space. Sociocultural realities can play the role of a barrier or a favorable environment for information and communication technologies in the educational sphere. Consequently, educational systems are being transformed in today's dynamic world along with other spheres of social activity, actively using digital potential. At the same time, cultural traditions are a stabilizing factor in innovation processes, which allows us to clearly position the role and status of the digital environment in the educational space. The use of ICT has its own characteristics and determines the priorities of future educational strategies. Conclusion. Therefore, maintaining a balance between the classical educational system and new educational environments is the key to the harmonious development of this sphere of social activity in the context of socio-cultural progress.
The role of a modern teacher's personal learning environment in improving the teaching of fundamental theoretical and clinical disciplines

The purpose of the study. The article focuses on the role of a properly organized personal learning environment of a modern teacher, performed at the expense of building an intellectual map using the xmind program in improving the teaching of fundamental theoretical and clinical disciplines. The specificity of the topic is an analytical approach to the application of the research method - descriptive comparison - for the analysis, synthesis and generalization of the role of a properly organized personal learning environment of a modern teacher in the possibility of significantly improving the mastery of the leading theoretical and clinical disciplines by streamlining the organization of all types of work of a modern teacher. Scientific novelty. For the first time, an original, innovative, alternative approach was put into practice, which shows that a properly organized personal learning environment of a modern teacher contributes to the effective formation of highly professional competencies. Conclusion. The introduction into the educational process of a properly organized personal learning environment of a modern teacher, performed at the expense of building an intellectual map using the xmind program, makes it possible to achieve the leading interests of fundamental theoretical and clinical disciplines in-depth knowledge of the general laws of disease development, pre-disease, to ensure their leading role in the formation of students' fundamentals clinical thinking and improving the quality of the educational process.
Culture in Design of Coding Toolkits for Young Learners in Developing Economies in Africa: A Review

With the increasing importance and demand of coding skills in today’s digital world, developing economies in Africa are putting every effort to include coding education in their educational curriculum. However, the existing coding toolkits for young learners have different cultural orientation making it hard to learn and use thereby making coding education programs and learning outcomes ineffective. The aim of the study was to carry out systematic literature review with particular emphasis on learning environment and pedagogy, use of local language and gender related norms and explored the potential challenges with recommendations in building culturally responsive coding kits. It was found out that the design of culturally responsive coding toolkits has the potential to improve the accessibility, affordability, relevance and effectiveness of coding education for young learners in developing economies in Africa contributing to more effective coding education and therefore helping to bridge the digital divide.
Federated adaptive reweighting for medical image classification

Medical data sharing across institutes is crucial to large-scale multi-center studies and the development of real-world AI applications but suffers from serious privacy issues. A promising solution to address this challenge is federated learning, which typically aggregates a global model from heterogeneous data spread across numerous clients without exchanging data. However, the traditional federated learning algorithm (i.e., FedAvg) merely aggregates the locally distributed models according to the amount of data on each client and lacks the consideration of data heterogeneity. In this paper, we propose a novel Federated Adaptive Reweighting (FedAR) algorithm for medical image classification. FedAR employs a flexible re-weighting scheme that can balance adaptively the contributions of the amount of data and the performance of the local model on each client to the weight of that client. Specifically, we allow the amount of local data to contribute more to the weight of each client in the early training stage and let the performance of the local model play a more important role in the late stage. We have evaluated the proposed FedAR algorithm against the locally trained model, globally trained baseline, and two existing federated learning algorithms on the ISIC2018 dataset and Chest X-ray14 dataset under the settings with a variable number of clients. Our results suggest that FedAR is an effective federated learning algorithm that substantially outperforms existing federated learning approaches.
PENGARUH MEDIA BONEKA TANGAN TERHADAP KETERAMPILAN MENYIMAK SISWA KELAS VI SDN 15 RAMBUTAN

The purpose of this study was to determine the effect of hand puppet media on the listening skills of the sixth grade students of SDN 15 Rambutan. By using the research method pre-experimental design with the type of one group pretest posttest. With a research population of 20 students of class VI. The sample in this study was the entire population with an average pretest score of 50.25 and an average posttest score of 81.20. The collection of research data using evaluation sheet learning outcomes. Data analysis used the Mann Whitney non-parametric test. The results in this study were the influence of hand puppet media on the listening skills of class VI students at SDN 15 Rambutan because Asymp.Sig (2-tailed) &lt; 0.05, namely 0.000 &lt; 0.05.
My Husband, there are Two Selections for you! Do you want to be Miserable as Shown in (025-028)? Or do you wish to be Happy as Shown in (029-032)? (Tcheonzamun 017th-032nd)

French missionary Dallet (1874) wrote in his book that ‘The thousand character essay’ had been utilized as a textbook for instructing Chinese character for the children in old China. ‘The thousand character essay’ is called as ‘Tcheonzamun’ in Korea. The present researcher chose 16 Chinese letters, and those 16 letters composed a poem of ‘The thousand character essay’ (Tcheonzamun 017th-032nd). For example, &lt;017-020 寒 (Han) 來 (Lae) 暑 (Seo) 往 (Wang)&gt; is a line. The present researcher used two translating methods. The first one is to utilize Korean pronunciation of Chinese character, and the second one is to use the meaning of Chinese character. There is another one method. It is to delete same part(s) of a Chinese character on the same line. At present, the researcher translated this poem through the second method. The book of Tcheonzamun by Han (1583) was taken as a textbook for this study. The title of this manuscript is ‘My husband, there are two selections for you! Do you want to be miserable as shown in (025-028)? Or do you wish to be happy as shown in (029-032)?’ The result of this study on the poem of ’The thousand character essay’, (Tcheonzamun 017th-032nd) was described as follows. &lt;Number in Tcheonzamun Chinese characters (the pronunciation on Korean language and written in English alphabet)&gt; 017-020 寒 (Han) 來 (Lae)-土=小人 暑 (Seo) 往 (Wang)-土=彳人 It is well known, the next phrase. "In order to give the warm condition (暑) to the slow walker (to the husband) (彳人), the smaller person (the wife) must have the cold condition (寒)." 021-024 秋 (Tchu) 收 (Su) 冬 (Dong) 藏 (Zang) But, this saying it is not true. It is not right! My dear Darling My husband! If you want to take (收) the best thing in your whole life (秋), you must do the good behavior (藏) to me your wife in common days, especially in the difficult time (冬) for me your wife! My husband, there are two selections for you! Do you want to be miserable as shown in (025-028)? Or do you wish to be happy as shown in (029-032)? 025-028 閏 (Yun) 餘 (Yeo) 成 (Seong)-戈=刀 歲 (Se)-戈=山广小 My husband! Even though you are the rich man (餘), if you scold (刀) your wife (小) in your house (广) and in the outdoors (山), you might soon be the poor man (閏). 029-032 律 (Yul)-聿=彳 呂 (Yeo)-口-口=丶 調 (Zo) -口-口-亠-二-土=几 陽 (Yang) My husband! Do you want the splendid thing like the shooting star (丶) to occur to you the slow walker (彳)? I am your wife, and I am shining like the sun (陽), while you are the man who has nothing (几). My husband, I can make you with my sincere love to be the happiest person in this world!
An automated malaria cells detection from thin blood smear images using deep learning

Timely and rapid diagnosis is crucial for faster and proper malaria treatment planning. Microscopic examination is the gold standard for malaria diagnosis, where hundreds of millions of blood films are examined annually. However, this method's effectiveness depends on the trained microscopist's skills. With the increasing interest in applying deep learning in malaria diagnosis, this study aims to determine the most suitable deep-learning object detection architecture and their applicability to detect and distinguish red blood cells as either malaria-infected or non-infected cells. The object detectors Yolov4, Faster R-CNN, and SSD 300 are trained with images infected by all five malaria parasites and from four stages of infection with 80/20 train and test data partition. The performance of object detectors is evaluated, and hyperparameters are optimized to select the best-performing model. The best-performing model was also assessed with an independent dataset to verify the models' ability to generalize in different domains. The results show that upon training, the Yolov4 model achieves a precision of 83%, recall of 95%, F1-score of 89%, and mean average precision of 93.87% at a threshold of 0.5. Conclusively, Yolov4 can act as an alternative in detecting the infected cells from whole thin blood smear images. Object detectors can complement a deep learning classification model in detecting infected cells since they eliminate the need to train on single-cell images and have been demonstrated to be more feasible for a different target domain.
Sistem Rekomendasi Program Studi Sarjana Berbasis Machine Learning Untuk Model Klasifikasi Calon Mahasiswa Baru

The Recommendation System can produce system requirements data that is more descriptive and easy to implement into software. Recommendation methods are combined to form more comprehensive recommendations based on fermat points. The education sector has never been indifferent to new technologies, and eventually switched to using the Internet. Prior to conducting this research, a review was carried out on various previous research results related to the lack of the role of knowledge space and user preferences in the data visualization recommendation system [3]. Broadly speaking, this study uses the method of recommending the Analysis and Discussion system. One of the main elements that must be considered in the system analysis stage is software problems, because the software used must be in accordance with the problem to be solved. In this stage, the search and collection of data and knowledge obtained by the expert system are carried out. A machine learning-based recommendation system for undergraduate study programs can help prospective new students choose the right study program according to their interests and talents. The classification model used can produce fairly high accuracy in recommending undergraduate study programs to prospective new students.
Gerakan Tangan Pemain Otomatis Menggunakan Computer Vision

Gesture recognition allows users of computer science technology to connect with their digital devices more conveniently. Technology for gesture recognition can be helpful in a variety of contexts, such as automated household appliances, automobiles, and interpretation of hand gestures. Gesture recognition is part of gesture recognition which determines what message a certain hand movement wants to convey. In developing this automatic hand movement we use segmentation and object detection where this method involves using algorithms to detect and identify objects or areas related to hand movements. , such as human skin, fingers, and others. Detection of human hand movements using computer vision is a digital image processing technique that aims to recognize human hand movements from image or video data. This technique can be applied in various applications such as human-computer interaction, hand gesture recognition, or video games. Making Automatic Player Hand Movements Using Computer Vision has the potential to improve the user experience when playing games or using interactive applications that require hand movements, according to the research and development that has been done. Games could be controlled more precisely and with less need for additional hardware such as joysticks or controllers if computer vision technology was able to accurately distinguish hand movements.
THE EDUCATIONAL AND UPBRINGING FUNCTIONS OF CHILDREN'S MUSICAL THEATRE IN THE INCLUSIVE EDUCATION ENVIRONMENT

The initial hypothesis of this article is to determine the educational and upbringing functions of children's musical theatre in the conditions of inclusive education as a triad: supervisor-director, participants-performers, and parent audience. Each of these links in the triad creates an expressive subsystem, and its comprehensive complex is subordinated to the sphere of the educational-artistic context of the emergence and implementation of both literary and musical creative concepts since the multifaceted problem of synthesizing arts has been and remains an actual problem of scientific research. A detailed description of the musical sound palette confirmed the validity of our research regarding the objective realization of musical works in performance as a procedural process in the formation of art images of sounds and words, the diversity of their perception of meaning by performers, which is an extraordinary factor in the formation of stage images in a play involving children and adolescents with special needs. Taking this into account, the director should rely on his entire previous background, worldview, general cultural, aesthetic, and pedagogical experience to develop the creative activity of children through theatrical activities, considering their psychological and physical peculiarities.&#x0D; The purpose of the article is to actualize the role of children's musical theatre as a genre-forming extracurricular institution in the conditions of inclusive education, to determine its educational and upbringing functions, to study the peculiarities of stage action in the artistic reproduction of images, to reveal the significance of the musical palette as an expression of the artistic idea for creating a creative atmosphere of the performance based on artistic-pedagogical experience, and to determine the cognitive needs of children and adolescents with special developmental needs through theatrical activity.
THE INFLUENCE OF EDUCATIONAL ENVIRONMENT ON THE DEVELOPMENT OF FUTURE DESIGNERS’ CREATIVITY

This scientific article is aimed at studying the problem of fostering creativity in future designers in the context of labour market requirements and taking into account the latest trends in design. The analysis of modern approaches to the educational process in the field of design at the institutional level and the compliance of educational services with the needs of the labor market was carried out. It was found that the creative educational environment of the educational institution best contributes to the development of creativity in future designers. The determining factors of the educational environment are revealed. It has been proven that educating students in a creative educational environment affects their creativity and further motivation for success. A conclusion was made about the need to create a creative and innovative educational environment in educational institutions.
Cali-NCE: Boosting Cross-modal Video Representation Learning with Calibrated Alignment

With the large-scale video-text datasets being collected, learning general visual-textual representation has gained increasing attention. While recent methods are designed with the assumption that the alt-text description naturally conveys the meaning and context of the video in semantics (i.e. well aligned with each other), it is unlikely to be satisfied for the Internet data, which potentially harms the quality of the learned visual-textual representation. To address this challenge, we first revisit three mainstream approaches: correspondence modeling, contrastive learning and predictive coding, demonstrating that a simple co-training strategy with these methods leads to a clear improvement in performance. To further explore the complementary nature of different training strategies, we propose a simple yet effective joint training framework that factorizes the total objective into conditional ones, termed as Cali-NCE <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> . Our method first estimates confidence scores for measuring the correspondence between video and text descriptions, and the scores are later used to calibrate the sample weightings during contrastive training. Through extensive experiments, we show that the proposed approach achieves state-of-the-art performance on multiple downstream tasks: text-to-video retrieval, video action recognition, and video retrieval.
Defending Low-Bandwidth Talking Head Videoconferencing Systems From Real-Time Puppeteering Attacks

Talking head videos have gained significant attention in recent years due to advances in AI that allow for the synthesis of realistic videos from only a single image of the speaker. Recently, researchers have proposed low bandwidth talking head video systems for use in applications such as videoconferencing and video calls. However, these systems are vulnerable to puppeteering attacks, where an attacker can control a synthetic version of a different target speaker in real-time. This can be potentially used spread misinformation or committing fraud. Because the receiver always creates a synthetic video of the speaker, deepfake detectors cannot protect against these attacks. As a result, there are currently no defenses against puppeteering in these systems. In this paper, we propose a new defense against puppeteering attacks in low-bandwidth talking head video systems by utilizing the biometric information inherent in the facial expression and pose data transmitted to the receiver. Our proposed system requires no modifications to the video transmission system and operates with low computational cost. We present experimental evidence to demonstrate the effectiveness of our proposed defense and provide a new dataset for benchmarking defenses against puppeteering attacks.
Learning CLIP Guided Visual-Text Fusion Transformer for Video-based Pedestrian Attribute Recognition

Existing pedestrian attribute recognition (PAR) algorithms are mainly developed based on a static image. However, the performance is not reliable for images with challenging factors, such as heavy occlusion, motion blur, etc. In this work, we propose to understand human attributes using video frames that can make full use of temporal information. Specifically, we formulate the video-based PAR as a vision-language fusion problem and adopt pre-trained big models CLIP to extract the feature embeddings of given video frames. To better utilize the semantic information, we take the attribute list as another input and transform the attribute words/phrase into the corresponding sentence via split, expand, and prompt. Then, the text encoder of CLIP is utilized for language embedding. The averaged visual tokens and text tokens are concatenated and fed into a fusion Transformer for multi-modal interactive learning. The enhanced tokens will be fed into a classification head for pedestrian attribute prediction. Extensive experiments on a large-scale video-based PAR dataset fully validated the effectiveness of our proposed framework. Both the source code and pre-trained models will be released at https://github.com/Event–AHU/VTF_PAR.
Integrated Financial Management Assistance through E-DAMS Application Development at Mukhtar Syafa’at Blokagung Islamic Boarding School, Banyuwangi

This community service research focuses on addressing financial management challenges faced by PP Mukhtar Syafa'at, an Islamic boarding school in Banyuwangi. Established in 1990 with a substantial student population, the school grappled with manual financial recording, leading to errors, omissions, and decentralized contributions handling. This study employed Participatory Action Research (PAR) to implement an integrated financial management solution, introducing computerized recording and an accompanying application. As a result, the school transitioned from a manual to an integrated system, bolstered by computerized recording and a financial reporting application, enhancing administrative accountability and accuracy in financial reporting.
Prediksi Pelabelan Rating AC Efisiensi Energi Menggunakan Pemodelan Machine Learning

The purpose of this research is to analyze data and perform machine learning modeling to predict the energy efficiency rating of air conditioning (AC) units using a labeled AC dataset from the Directorate General of New, Renewable and Energy Conservation (EBTKE). The data consists of Power, Cooling Capacity, Efficiency, Annual Energy Consumption, and Electricity Cost. The data is visualized using box plots and linear regression to examine the relationship between the dependent variable (Rating) and the independent variables. The analysis shows that the Efficiency variable has the greatest impact on the Rating, with a linear regression coefficient value of 0.75. Then, the machine learning model using the decision tree method is tested using 5-fold K-fold validation. The evaluation results of the model show a mean absolute error (MAE) of 0.2, mean squared error (MSE) of 0.4, root mean squared error (RMSE) of 0.63, and accuracy of 0.9. Based on these results, it can be concluded that the machine learning model using the decision tree method can be used to predict the energy efficiency rating of AC units with a satisfactory level of accuracy. However, to improve the accuracy of the predictions, it is necessary to increase the amount of data used in the modeling.