Reviewerly/exHarmony huggingface dataset:
UR-Net: An Integrated ResUNet and Attention Based Image Enhancement and Classification Network for Stain-Free White Blood Cells

The differential count of white blood cells (WBCs) can effectively provide disease information for patients. Existing stained microscopic WBC classification usually requires complex sample-preparation steps, and is easily affected by external conditions such as illumination. In contrast, the inconspicuous nuclei of stain-free WBCs also bring great challenges to WBC classification. As such, image enhancement, as one of the preprocessing methods of image classification, is essential in improving the image qualities of stain-free WBCs. However, traditional or existing convolutional neural network (CNN)-based image enhancement techniques are typically designed as standalone modules aimed at improving the perceptual quality of humans, without considering their impact on advanced computer vision tasks of classification. Therefore, this work proposes a novel model, UR-Net, which consists of an image enhancement network framed by ResUNet with an attention mechanism and a ResNet classification network. The enhancement model is integrated into the classification model for joint training to improve the classification performance for stain-free WBCs. The experimental results demonstrate that compared to the models without image enhancement and previous enhancement and classification models, our proposed model achieved a best classification performance of 83.34% on our stain-free WBC dataset.
Outdoor environmental education in the contemporary world

Click to increase image sizeClick to decrease image size AcknowledgmentsThe authors acknowledge the following institutions, namely Universitas Riau, Universitas Pendidikan Indonesia and the Indonesian Researchers for Language Learning and Teaching (iRecall), who support the publication of this article.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsRola Angga LardikaRola Angga Lardika is a lecturer in the Department of Sport Education at Universitas Riau, Pekanbaru, Indonesia and a PhD student at Universitas Pendidikan Indonesia, Bandung, Indonesia, sponsored by Beasiswa Pendidikan Indonesia Lembaga Pengelolaan Dana Pendidikan (BPI-LPDP/the Indonesia Education Endowment Fund for Education) under the Ministry of Finance of the Republic of Indonesia. Currently, he serves as chairman of the Association of Sports Physiology Experts (PAIFORI) in Riau Province. His research interests include developing sports education materials, sport science, physical activity, physical education, outdoor education and exercise physiology.Fikri YandaFikri Yanda is a PhD student in the Department of English Language Education at Universitas Pendidikan Indonesia, Bandung, Indonesia, sponsored by Lembaga Pengelolaan Dana Pendidikan (LPDP/the Indonesia Education Endowment Fund for Education) under the Ministry of Finance of the Republic of Indonesia. He currently serves as the president of the Indonesian Researchers for Language Learning and Teaching (iRecall). His current research project for dissertation is about the relationship of spirituality or religion and language education. His research interests include language materials development, identity and spirituality within language education in religious-based educational institutions.Beltasar TariganBeltasar Tarigan is a Professor Of Sport Pedagogy and Sport Physiology (Faculty of Sport and Health Education) at Universitas Pendidikan Indonesia. Prof. Beltasar Tarigan is an expert in the fields of Sport Pedagogy and Sport Physiology. Theoretically, the implications of this field of expertise are used to collect and develop various theoretical information in the form of scientific works, such as books, teaching materials, modules and published articles on a national and international scale. Practically, it has been practiced in coaching or refreshing physical education teachers both at regional and national levels.
Mixed media in neo-academic art objects

The study of the artistic heritage of neo-academicians in the context of the study of mixed techniques is quite relevant. To date, the analysis of the creativity of artists, representatives of non-academism as an artistic trend of the late twentieth century in Russia, is based on the artistic criticism of art critics, art critics who were part of this trend and considered the work of non-academicians from the perspective of the artistic life of this period in the context of the socio-cultural processes of Russia during the Perestroika era. Also, the works of neo-academist artists are studied from the position of "creative rebellion" and the search for new forms in art. In this article, the works of T. Novikov, G. Guryanov, K. Goncharov, V. Mamyshev-Monroe and other representatives of NAII are studied from the position of "mixed techniques" in art objects. The main emphasis is placed on the analysis of art objects in mixed techniques in the context of overcoming formalism, embodying stylistic diversity, metamorphosis of forms and states, pictorial symbols and universal meanings. The realization of the principle of the infinity of choice and the infinity of meaning and diversity is associated with postmodernism in art, the introduction to which became decisive in Russian art of the late twentieth and early twenty-first centuries. The appeal to the study of art objects of neo-academicians made in mixed technique allows us to enrich and supplement the understanding of the term "mixed techniques" in modern art practices related to the search for new forms, compositional solutions, the formation of a unique author's language, the originality of the work.
Analysis of Potential Educational Areas of Pokémon Go! Game Use Based on Mini FGI Method

This article attempts to determine the educational nature of “Pokémon Go!” game based on user interactions with virtual space and real-life elements. For this purpose, interviews with players in mini focus groups (mini FGI) were the chosen method. Respondents were asked about their interaction with actual objects that are reflected in the game, how they search for information about the locations themselves, and about the educational content in the game space. The players were also asked for their ideas on how to enhance the educational potential of the game, as such opinion of real-life players was deemed notable.&#x0D; Based on the results obtained, firstly, areas of potential educational value that still need to be improved were identified and, secondly, recommendations were formulated how to enhance the educational opportunities arising from the game.
Implementation of the Qiroati Method in Improving Quran Literacy at SDIT al Madinah Karawang

The Qiroati method is a method of learning to read the Koran which directly practices tart reading in accordance with the qoidah of practical recitation. One of the obstacles in the process of learning to read the Koran in general is that the teacher does not use the method, only reads normally. Therefore there are still some students who are not fluent in reading the Koran because they feel the method used is less effective, unstructured and seems monotonous and makes students feel bored in the process of learning to read and write the Koran. This research is intended to find out how the application of the Qiroati method through BTQ learning improves the ability to read the Koran in students at SDIT Al Madinah Karawang. This type of research is field research. In this study, the researcher will describe the application of the Qiroati method through BTQ learning in improving the ability to read the Koran. While the nature of the research is descriptive in nature. Data collection techniques used are interviews, tests and documentation. For data analysis techniques used are data collection, presentation and conclusion. The results of research conducted by researchers can be concluded that the Qiroati method can improve students' Al-Quran reading skills with evidence that students get good grades when reading the Al-Quran test. The implementation of the Qiroati method is by the way the teacher exemplifies correct reading which then students read together. So that with the Qiroati method students can find out how to read correctly.
Applying the SWMM Software Model for the High Potential Flood-Risk Zone for Limited Catchments in Erbil City Governorate

Every year, the vicinity of the Council of Ministers is frequently inundated. Due to the area's shifting land use and the inadequacy of the existing drainage system to handle the rising drainage loads, KRG decided to build two box sewers (BS). The drainage system in the study area will be evaluated, and the effectiveness of the BS construction in reducing flood amounts in the study area, as well as comparing the capacity of the drainage system before and after the BS construction using EPA SWMM version 5.2. The data used in this study are rain data and drainage network dimensions. Since the rain gauge station at the research area did not directly provide the 2-hour time series rainfall data, it was created using the Alternating Block Method (ABM) by determining a rainfall hyetograph from 5-year, 25-year, and 100-year Intensity-Duration-Frequency (IDF) curves. Following the specification and inputs of all EPA SWMM 5.2 parameters, six simulation scenarios were run based on the before and after adding (BS). Prior to the addition of (BS), the number of flooded nodes for the first three scenarios was (33, 31 and 28), and it was reduced to (25, 22 and 19) nodes. According to the findings, the drainage planning design for the study area is not adequate to handle the drainage load of the area, either now or in the future.
Rancang Bangun Peringatan Dini Bahaya Banjir Pada Daerah Aliran Sungai Berbasis Internet Of Think

High rainfall, High rainfall, especially during the rainy season, results in a rise in the level of water flowing into the river, which can be a triggering factor for the danger of flooding. One indication that can be known is the overflow of water in the river flow so that the flowing water cannot be accommodated by the river canal. In this study, a monitoring system can provide water level reading information using the HC-SR04 ultrasonic sensor with the addition of a flow meter sensor reading feature, and a DHT11 temperature sensor. This flood early warning system is designed to provide a warning when a flood hazard will occur which is indicated by an indication of rising water levels in the river flow with information directly or in real time as a disaster early warning effort. This information will then be displayed on a 16x2 LCD, alarm, and smartphone direct display via Internet of Think technology with ESP8266 as the transmission medium to the cloud network. In addition to presenting information, the tool is also equipped with a servo motor that will activate the opening of the sluice gate so that the water level returns to normal. In the appearance of this information later, the system will display the state of the level of early warning information with a red LED indicator display and a buzzer that lights up when conditions are dangerous and can be accessed via a smartphone. With this tool designed later, it is hoped that it will be able to anticipate the danger of flooding that will occur so that it can help residents around the riverbanks to get early warning when a possible flood hazard will occur.
The Psychological Basis of Shaping the Mathematical Competences of Students (9th Grade) in Education Ukrainian Language

The article examines the psychological foundations of Ukrainian language learning. The psychological components that ensure students master a dynamic combination of mathematical and communicative skills, ways of thinking and a number of characteristics (memory, attention, perception, imagination, self-improvement, decision-making) for comprehensive personal development are outlined. The main skills (analysis, argumentation, comparison, generalization, abstraction, specification, etc.) that influence the success of basic education students in learning the Ukrainian language are highlighted.
Occurrence Frequency of Rhetorical Moves in Introductions of Linguistics Research Articles From Non-Scopus and Scopus Journals

Serving as a fundamental opening section, the research article introduction (RAI) provides an entrance to a certain topic in the exploration of the unknown content of the research. It is a manifestation of rhetorical maneuver and establishes the context, identifies the challenges, and outlines the rationale for the study. Therefore, it is vital to make a well-crafted RAI to catch readers’ attention. However, the disparities in rhetorical moves employed in English linguistics RAIs between non-Scopus-indexed and Scopus-indexed journals have received less scrutiny. The present study aims to investigate the rhetorical move structures in both types of corpora. The non-Scopus and Scopus corpus each contained 50 RAIs. Based on the adapted Swales’ (1990) Create-A-Research-Space (CARS) model, the occurrence frequency of moves and steps was first analyzed, and the relationship between the frequency of moves and steps and the indexing of journals was then explored. The findings showed that the most frequent move in both corpora was Move 1, followed by Move 3 and Move 2. However, the higher number of overall moves in the non-Scopus corpus suggested that there was an overuse of moves by the less experienced writers, and through Chi-square, Move 3 Step 1B (announcing present research) was detected to have a significant relationship with the indexing of journals. The findings of this study pave the way for writers to construct well-organized RAIs and get their papers published in the field of linguistics.
Proposing a Model for Developing Facilities to Support STEM-Oriented Natural Science Experiences in Junior High Schools in Vietnam

In Vietnam, in the context of a fundamental and comprehensive renovation of education in the spirit of transforming from content-based education to education that develops the quality and capacity of learners; STEM education and experiential activities are encouraged to be implemented in schools from preschool, elementary, middle, and high school levels. Besides, Natural Science is an integrated subject between Physics, Chemistry, and Biology; is a convenient subject for organizing and implementing STEM education-oriented experiential activities. The STEM education-oriented natural science experience is a new educational model, and schools still face many physical difficulties when implementing practical activities, experiments, and scientific research, modeling Physics, Chemistry, and Biology. From that, it can be seen that the facilities are one of the factors contributing to the success of the operation. Therefore, it is necessary to propose a management model for the purpose of developing facilities in schools in order to create favorable conditions for teachers to implement STEM education-oriented natural science experiences. On the basis of theory, the research paper proposes a model of infrastructure development that contributes to supporting STEM experiences in natural sciences at the lower secondary level. The research results suggest the content and implementation method of surveying, planning, organizing, directing, and checking the implementation results. The research gives meaning to education managers to apply theory to practice to develop facilities in schools, contributing to improving the quality of education in the locality and national education.
Development of Android Animate CC-Based Interactive Learning Media at SMAN 1 Barusjahe, North Sumatera

This study aims to develop and comprehend the quality and the effectiveness of Android Animate CC as learning media in class XI at SMAN 1 Barusjahe. This study uses the research and development based on the ADDIE consisting of five stages, namely analysis, design, development, implementation, and evaluation. Before knowing the feasibility being tested on the students, there is a validation test on the teaching materials and media aspects. The average score of material validation reached 89.5% while the score of media value is noted to gain 92.4%; this gaining is included as the "very good" category. Then, to know its effectiveness, pre- and post-tests are carried out. The students’ average score after pre-test is 46.7 and the average score after post-test gained 82.8. The result shows that the average score of N-Gain (g) is 0.71 which is classified in the “high” category. So, the result indicates that the efficiency of using Android Animate CC is effective in the learning process. Keywords: learning media, android animate CC, French, development
Corrigendum: Multi-task learning based on Stochastic Configuration Networks

[This corrects the article DOI: 10.3389/fbioe.2022.890132.].
Communications: PhotonicsViews 4/2023

PhotonicsViewsVolume 20, Issue 4 p. 14-22 CommunicationsFree Access Communications: PhotonicsViews 4/2023 First published: 01 September 2023 https://doi.org/10.1002/phvs.202370404AboutPDF ToolsExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onEmailFacebookTwitterLinkedInRedditWechat Volume20, Issue4August/September 2023Pages 14-22 RelatedInformation
Relevant Visual Semantic Context-Aware Attention-Based Dialog

The existing dataset for visual dialog comprises multiple rounds of questions and a diverse range of image contents. However, it faces challenges in overcoming visual semantic limitations, particularly in obtaining sufficient context from visual and textual aspects of images. This paper proposes a new visual dialog dataset called Diverse History-Dialog (DS-Dialog) to address the visual semantic limitations faced by the existing dataset. DS-Dialog groups relevant histories based on their respective Microsoft Common Objects in Context (MSCOCO) image categories and consolidates them for each image. Specifically, each MSCOCO image category consists of top relevant histories extracted based on their semantic relationships between the original image caption and historical context. These relevant histories are consolidated for each image, and DS-Dialog enhances the current dataset by adding new context-aware relevant history to provide more visual semantic context for each image. The new dataset is generated through several stages, including image semantic feature extraction, keyphrase extraction, relevant question extraction, and relevant history dialog generation. The DS-Dialog dataset contains about 2.6 million question-answer pairs, where 1.3 million pairs correspond to existing VisDial’s question-answer pairs, and the remaining 1.3 million pairs include a maximum of 5 image features for each VisDial image, with each image comprising 10-round relevant question-answer pairs. Moreover, a novel adaptive relevant history selection is proposed to resolve missing visual semantic information for each image. DS-Dialog is used to benchmark the performance of previous visual dialog models and achieves better performance than previous models. Specifically, the proposed DS-Dialog model achieves an 8% higher mean reciprocal rank (MRR), 11% higher R@1%, 6% higher R@5%, 5% higher R@10%, and 8% higher normalized discounted cumulative gain (NDCG) compared to LF. DS-Dialog also achieves approximately 1 point improvement on R@<i>k</i>, mean, MRR, and NDCG compared to the original RVA, and 2 points improvement compared to LF and DualVD. These results demonstrates the importance of the relevant semantic historical context in enhancing the visual semantic relationship between textual and visual representations of the images and questions.
Feature Extraction Techniques for Facial Expression Recognition (FER)

Facial expression recognition (FER) is a significant area of study in computer vision and affective computing. In numerous applications, such as human-computer interaction, emotion detection, and behavior analysis. Feature extraction is a crucial stage in facial expression recognition systems, as it involves extracting pertinent information from facial images in order to accurately represent various facial expressions. The purpose of this paper is to investigate and compare the various feature extraction techniques used in facial expression recognition, as well as their merits, limitations, and impact on overall system performance. Using benchmark datasets and performance metrics, the evaluation provides insight into the efficacy of various feature extraction methods. In this study, we propose a method for facial expression recognition that integrates deep learning, Principal Component Analysis (PCA), and Gray Level Co-occurrence Matrix (GLCM). Use 1D-CNN for classification.
PENGEMBANGAN SISTEM INFORMASI ADMINISTRASI PERPUSTAKAAN SMA XI KOTA JAMBI

The library at SMA Negeri XI Jambi City in data processing still uses a recording system or conventional. In the process of processing the data by taking notes on books for members who want to borrow books from the library. And students sometimes forget when to return the book. Based on this, it is necessary to develop an information system that can provide accurate data, process data quickly and provide information to students to finally return books using a website information system. Development of this information system is the best solution in solving existing problems. at SMA Negeri XI Jambi City, as well as with a computerized system, an effective and efficient activity can be achieved in supporting activities in processing library data at this school.
Chunker Based Sentiment Analysis for Nepali Text

The article represents the Sentiment Analysis (SA) of a Nepali sentence. Skip-gram model is used for the word to vector encoding. In the first experiment the vector representation of each sentence is generated by using Skip-gram model followed by the Multi-Layer Perceptron (MLP) classification and it is observed that the F1 score of 0.6486 is achieved for positive-negative classification with overall accuracy of 68%. Whereas in the second experiment the verb chunks are extracted using Nepali parser and carried out the similar experiment on the verb chunks. F1 score of 0.6779 is observedfor positive -negative classification with overall accuracy of 85%. Hence, Chunker based sentiment analysis is proven to be better than sentiment analysis using sentences.
Quality Data Sharing Platform for Aviation Suppliers Using Blockchain Process

The aviation industry is characterized by complex supply chains, which can pose challenges for ensuring quality processes across all participants. To address this issue, a blockchain-based process quality data sharing platform has been proposed to improve the traceability and transparency of quality-related information among aviation suppliers. This platform allows suppliers to securely share process quality data, such as inspection results and certifications, with their partners in the supply chain. The platform utilizes a permissioned blockchain network, ensuring that only authorized parties have access to the shared data. Smart contracts are used to automate the validation and verification of data, reducing the need for manual intervention and streamlining the quality assurance process. The platform also incorporates a user-friendly interface to enhance ease of use and accessibility. Overall, the proposed platform has the potential to increase efficiency and trust in aviation supply chains by improving the sharing and verification of process quality data.