Reviewerly/exHarmony huggingface dataset:
The new digital education policy landscape: from education systems to platforms

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FedDroidMeter: A Privacy Risk Evaluator for FL-Based Android Malware Classification Systems

In traditional centralized Android malware classifiers based on machine learning, the training sample uploaded by users contains sensitive personal information, such as app usage and device security status, which will undermine personal privacy if used directly by the server. Federated-learning-based Android malware classifiers have attracted much attention due to their privacy-preserving and multi-party joint modeling. However, research shows that indirect privacy inferences from curious central servers threaten this framework. We propose a privacy risk evaluation framework, FedDroidMeter, based on normalized mutual information in response to user privacy requirements to measure the privacy risk in FL-based malware classifiers. It captures the essential cause of the disclosure of sensitive information in classifiers, independent of the attack model and capability. We performed numerical assessments using the Androzoo dataset, the baseline FL-based classifiers, the privacy-inferred attack model, and the baseline methodology of privacy evaluation. The experimental results show that FedDroidMeter can measure the privacy risks of the classifiers more effectively. Meanwhile, by comparing different models, FL, and privacy parameter settings, we proved that FedDroidMeter could compare the privacy risk between different use cases equally. Finally, we preliminarily study the law of privacy risk in classifiers. The experimental results emphasize the importance of providing a systematic privacy risk evaluation framework for FL-based malware classifiers and provide experience and a theoretical basis for studying targeted defense methods.
DEVELOPMENT OF LEARNING VIDEOS ON THE THEME OF ADVANTAGES AND LIMITATIONS BETWEEN SPACES AND THE ROLE OF ECONOMIC ACTORS IN AN ECONOMY CLASS VIII LEVEL SMP / MTS (Research Study: MTSN 5 Kediri, MTS Ma'arif Bakung, SMPN 3 Srengat)

Abstract: This research develops video media learning friends advantages and limitations between space and the role of economic actors in an economy even semester class VIII social studies junior high school / MTs research study: MTSN 5 Kediri, MTS Ma'arif Bakung, SMPN 3 Srengat. The development model used by Borg and Gall with 10 steps. With research subjects 33 students from MTS Ma'arif Bakung, 25 students from SMPN 3 Srengat and 32 students from MTSN 5 Kediri. Researchers collected data by observation and questionnaire. Data analysis techniques here researchers use qualitative descriptive analysis and descriptive statistical analysis. The results of this study indicate that the results of the needs analysis of researchers know that students pay less attention if the learning media uses books, the needs of students related to the media are also supported because of the existence of learning that was previously carried out online. With the existence of online learning that always uses mobile phones has an impact on the lack of interest in reading students to books, and educators are less varied in utilizing learning media, so it is necessary to develop a medium that is in accordance with the conditions of learning at school. The process of developing social studies learning videos on the theme of the advantages and limitations of inter-space and the role of economic actors in an economy of class VIII at the junior high school / middle school level can researchers go through well so as to produce a video media. Learning video media can be known level of validity at MTSN 5 Kediri obtained the results of Cronbach alpha 0.861, Mts Ma'arif bakung obtained the results of Cronbach alpha 0.823, SMPN 3 Srengat obtained the results of Cronbach alpha 0.921 which can be said to be reliable because it has obtained a Cronbach alpha value greater than 0.6. &#x0D;
COMPARATIVE ANALYSIS OF RUSSIAN AND FOREIGN THEORIES AND PRACTICES OF APPLICATION OF BLENDED LEARNING IN INSTITUTIONS OF HIGHER EDUCATION

The article explores a new pedagogical approach that has been gaining popularity in recent decades. This refers to a blened learning model that makes it possible to ensure the availability of higher education for various categories of students. Moreover, the transition to a new format of education was due to the unfavorable epidemiological situation in the world (Covid-19). To date, Russian and foreign researchers have made attempts to formulate the essence of this approach and the ways of its implementation in the educational process, however, theorized knowledge about blended learning and the practices of its implementation are still insufficient. For this reason, the organization of training in a blended format is still experimental. The article describes the experience of implementing a blended learning model in leading Russian and foreign universities, namely, the Massachusetts Institute of Technology, Imperial College London, the University of Maryland, Moscow State Institute of International Relations and Tomsk Polytechnic University. The teachers note that due to the fact that students study a part of the educational material on their own through information and communication technologies before the start of the classroom lessons, is freed up more time for analysis of received information. In this regard, the classroom lesson becomes a place for generating new ideas and proposals. Thus, when organizing blended learning, the role of the teacher changes – he acts not as a translator of ready-made knowledge, but as a consultant and adviser. Consequently, as a result of training, an independent personality is formed, capable of exploring and critically analyzing the information received.
PERANCANGAN MULTIMEDIA INTERAKTIF SEJARAH INDONESIA UNTUK S.D.K. SANTA MARIA IMMACULATA TABANAN

This article describes the interactive multimedia design as a learning medium to provide an innovative learning experience among students. Through media such as audio, video, animation, and the interaction between the media and students can help motivate students to do independent learning. Interactive Multimedia Design aims to introduce Indonesian history to 5th-grade students at S.D.K.Santa Maria Immaculata Tabanan Elementary School. The data used consists of field data and literature using a qualitative approach and collected using several methods such as interviews, observations, literature, and documentation. As a result, on observational at S.D.K.Santa Maria Immaculata Elementary School showed that there were obstacles regarding the lack of teacher skills in making learning media helping increase the effectiveness, efficiency, and interest in learning materials. In addition, in delivering the material on Indonesian history, students are only asked to read what is already in the book. With these obstacles and shortcomings, the author helps teachers to designing interactive multimedia using the explorer concept and cartoon visual style as an illustrative function and supporting media in providing a good understanding of the material to elementary school students.
NO-CODE WEB DEVELOPMENT

The rapid evolution of technology has led to the emergence of no-code web development, enabling individuals without programming expertise to create web applications.This research paper aims to explore the impact and potential of no-code web development in empowering non-programmers to participate in web development activities.The study adopts a mixed-methods approach, combining qualitative interviews with no-code developers and quantitative analysis of user satisfaction surveys.The findings reveal that no-code web development offers a user-friendly and accessible platform for creating web applications, reducing the reliance on traditional coding skills.The research further investigates the benefits and challenges associated with nocode development, highlighting its potential to democratize web development and foster innovation.The study concludes by discussing the implications of no-code web development for both individuals and organizations, emphasizing the need for further research and industry-wide adoption.Overall, this research contributes to the growing body of knowledge on no-code web development and its transformative effects on the digital landscape.
AirSOD: A Lightweight Network for RGB-D Salient Object Detection

Salient object detection (SOD) aims to identify the most prominent regions in images. However, the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">large model sizes</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">high computational costs</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">slow inference speeds</i> of existing RGB-D SOD models have hindered their deployment on real-world embedded devices. To address this issue, we propose a novel method named AirSOD, which is committed to lightweight RGB-D SOD. Specifically, we first design a hybrid feature extraction network, which includes the first three stages of MobileNetV2 and our Parallel Attention-Shift convolution (PAS) module. Using the novel PAS module enables capturing both long-range dependencies and local information to enhance the representation learning while significantly reducing the number of parameters and computational complexity. Secondly, we propose a Multi-level and Multi-modal feature Fusion (MMF) module to facilitate feature fusion, and a Multi-path enhancement for Feature Refinement (MFR) decoder for feature integration. The proposed method significantly reduces the model size by 63%, decreases the computational complexity by 43%, and improves the inference speed by 43% compared with the cutting-edge model (MobileSal). We test our AirSOD on six widely-used RGB-D SOD datasets. Extensive experimental results demonstrate that our method obtains satisfactory performance. The source codes will be made available.
Enhancing underwater images with medium-guided multi-color space embedding

Our strategy makes use of the unique characteristics of the underwater medium to direct the enhancing procedure.Using a scattering and absorption model based on physics, we first simulate the color distortion brought on by the water medium.This model describes how underwater circumstances affect color appearance and picture quality.We build a medium transmission (showing the fraction of scene light reaching the camera)guided decoder network inspired by underwater imaging physical models to improve network performance in low-quality locations.As a consequence, our network can successfully improve the visual quality of underwater photographs by combining the advantages of physical model-based and learning-based techniques.Extensive testing shows that our Ucolor outperforms cutting-edge approaches in terms of visual quality and quantitative factors.
Understanding the Social Commerce Scam and Consumers Self Disclosure

The proliferation of online shopping scams has become widespread in Malaysia and other parts of the world as e-commerce continues to grow in popularity. Malaysia is known for having many online shoppers and is considered a high-risk country, city, or region for online fraud. Recently, scammers have taken advantage of the new social media landscape known as social commerce or S-commerce, which has fewer regulations than legal online shopping websites. This trend has created ample opportunities for scammers to steal consumers' data and money. Unlike traditional online shopping scams, these scams involve data stealing, which can have severe consequences for the victims. This study examines how consumers disclose their personal information during online shopping via social commerce platforms. The research involved conducting in-depth interviews with eight informants who had experienced online shopping scams in the Klang Valley area. The study found that social commerce platforms have influenced consumers' self-control in disclosing their personal information as they can fulfil consumers' needs and wants leisurely. However, this has created room for scammers to manipulate consumers and trap them through social commerce activities.
Mindfulness in the Metaverse: Examinations into Women’s Well-being

This paper proposes a conceptual framework to study the potential of mindfulness to enhance women’s well-being. It hypothesizes that mindfulness skills developed through metaverse-based interventions will encourage mindful consumption practices and improve women’s well-being. Past literature review examines the emerging trends in the digital mental health domain. It reveals large gaps in intentions and behaviors for mobile-based health interventions and how immersive technologies can help to overcome such prevalent issues. The current paper’s scope of study can contribute meaningfully to literature regarding the Metaverse, especially, its potential to influence consumer attitudes, behaviors and well-being. Such findings can be effectively used by researchers, governmental agencies, corporates, and brands working to augment consumer well-being.
Research on writer identification based on vision transformer

The writer identification task infers the writer by analyzing the texture, structure, and other representative features of the handwriting. Inspired by the attention mechanism, an end-to-end writer identification model is proposed in this paper, which combines both global features and local features. The Vision Transformer is used as the backbone network, and the Convolutional block attention module (CBAM) is introduced to enhance the ability of global feature awareness of the model. The proposed method is evaluated on two public data sets, IAM and CVL respectively. In the task of word-level writer identification, the accuracy rates in two data sets were 90.1% and 92.3% respectively. In the task of page-level writer identification, the accuracy rates were 98.6% and 99.5%, as a state-of-the-art performance.
REMOVAL OF RAIN COMPONENTS FROM SINGLE IMAGES USING A RECURRENT NEURAL NETWORK

Context. Removing the undesirable consequences of rain effects from single images is an actual problem in many computer vision tasks, because rain streaks can significantly degrade the visual quality of images and seriously interfere with the operation of various intelligent systems, which are used for their processing and further analysis.&#x0D; Objective. The goal of the work is to develop a method for detecting and removing undesirable effects of the rain from single images, which is based on the using of a convolutional neural network with a recurrent structure.&#x0D; Method. The main component of the proposed method is a convolutional neural network, which has a recurrent multi-stage structure. A feature of this network architecture is the use of repeated blocks (layers), at the output of which you can get an intermediate result of «cleaning» the original image. Moreover at the output of each next layer of the network we get an image with less influence of rain components than on the previous one. Each network layer contains two independent sub-networks (branches) for parallel image processing. The main branch is designed to detect and remove the effect of rain from the image and the attention branch is used to improve and speed up the process of detecting undesirable rain components (for rain attention map formation).&#x0D; Results. An approach has been developed to automatically detect and remove the rain effect from single images. The process of “cleaning” the original image is based on the use of a convolutional neural network with a recurrent structure, which was trained on the Rain100H and Rain100L datasets. The results of computer experiments, which testifies to the effectiveness and expediency of using the proposed method for solving practical tasks of pre-processing “contaminated” images are presented.&#x0D; Conclusions. The advantage of the developed method for removing undesirable components of rain from images is that the recurrent multi-stage network architecture, on which it is based allows it to be potentially applied to solving tasks under conditions of limited computing resources. The proposed method can be successfully used in the development of intelligent systems for area monitoring with surveillance cameras, autonomous vehicles control, processing aerial photography results, etc. In the future, it should be considered the possibility of forming a separate sub-network to eliminate blurring in the image and train the network on datasets that contain image samples with different components of rain, which will make the method more «resistant» to different forms of the rain effect and increase the quality of image “cleaning”.
Analysis of search engines of open access institutional repositories

Introduction: Scientific communication in its new model of performance, openly enabling access to information, has contributed that society can resort to scientific production in an easier way, which has occurred due to its availability in open access journals and institutional repositories. In a scientific context, the retrieval of information provides access to intellectual production from the possibility of its search in retrieval systems. Objective: To analyze the information retrieval systems (IRS) based on the search tools of the Brazilian institutional repositories of theses and dissertations available in the BDTD and its databases, comparing them with the parameters established by IBICT. Methodology: Conducts bibliographic research on the theme and documentary research from access to the standards, guidelines, and manuals provided by IBICT.Results: It confirms that the institutions participating in the BDTD do not necessarily need to stick to the standards in a partial way established by IBICT, being necessary only that they assign to their repositories the mandatory metadata standards, along with the use of the OAI-PMH protocol and the use of XML technology so that the collection of data occurs for availability in the national BDTD portal. Conclusion: The information retrieval systems of the repositories have technological tools and specifications that confer navigation in the systems by the users, contributing to the best search experience and access to information relevant to their informational issues.
Numerical demonstration of spatial photonic Ising machine by using time-division multiplexing

In this study, we present a method for enhancing a function of the spatial photonic Ising machine by using time-division multiplexing. Processing of multiple signals in which spin interaction is encoded provides the representation of the Ising Hamiltonian which functions as an indicator to solve combinational optimization problems. To evaluate the performance of the proposed system, we calculated the Ising Hamiltonian by simulating light propagation. We confirmed that the optimal solution of a given Knapsack problem is effectively obtained by the proposed system.
Cataloging in a Children’s Hospital Library: A Case Study in a Brazilian Public Hospital

Cataloging is an essential activity of a children’s hospital library used not only to identify and retrieve bibliographic resources, but mainly to protect its users: hospitalized child and accompanying adult. The child is in a situation of extreme vulnerability, in which reading a mis-indicated book may harm him/her, while an appropriate book may help his/her recovery. In this paper, metadata is introduced to indicate the most appropriate user profile for each book. In addition, the design and cataloging process in the children’s hospital library of a Brazilian public hospital are detailed, including specific software and experimental results for cataloging.
AN EXAMINATION OF PROBLEMS ENCOUNTERED IN TRANSPORTED EDUCATION

The purpose of this study is to examine the research conducted on the problems encountered in transportation education and to provide suggestions for solutions based on the findings regarding the problems faced by administrators, teachers, students, and parents. The research method used in this study is literature review, and the scope of the study is based on articles, theses, and books published in the literature related to transportation education. Document analysis was used as the data collection tool. During the data collection process, articles and theses published in the literature related to the research problem and sub-problems were searched online, and books related to the topic were examined. The data obtained from the documents were organized as the problems encountered by administrators, teachers, students, and parents in schools where transportation education is provided, and these data were compared by correlating them. Based on the data obtained during the research, it was found that the problems encountered by administrators include transportation services, meal services provided to students, and the extra workload imposed by the system. Teachers within the education system can face many difficulties, including heavy duties such as shift work, extra workload imposed by the system, and communication problems with parents. Students can also experience problems related to transportation services and meal services provided. Particularly in schools providing transportation education, parents may face difficulties in terms of distance from their homes to the schools and the lack of transportation opportunities for some parents.
Deluges of Data Are Changing Astronomical Science

Astronomers today are more likely than ever to access data from an archive rather than travel to a telescope—a shift that’s democratizing science.
Combining the strength of Petroleum and Mineral System knowledge to advance exploration within the Critical Mineral space

Both the petroleum and mineral industries have relied on proven methods when exploring for economic deposits. All methods have their origins in a deep understanding in geological principles, so it’s no surprise that there are many analogous processes employed across both industries. A significant difference is “where” in the earth’s crust the commodity of interest is accumulated and extracted. Economic recovery of any resource drives “how” explorers go about finding the commodity of interest and what tools they employ in their search.
Possible Late Mesoproterozoic or earliest Neoproterozoic glacial deposits, Beetaloo Sub-basin, Northern Territory

In the Beetaloo Sub-basin, the Kyalla Formation is unconformably overlain by a late Mesoproterozoic to early Neoproterozoic sandstone to mudstone succession comprising three formations/units: the lower Jamison sandstone, the upper Jamison sandstone, and the Hayfield mudstone (Munson, 2016; pers. comm. 2022). Gorter and Grey (2013) subdivided the Jamison sandstone into two mappable units separated by an unconformity. The Jamison sandstone and overlying Hayfield mudstone represent a marked change in provenance and were deposited after the Musgrave Orogeny in a basin dominated by silciclastic sedimentation that may have formed a shallow, long-wavelength foreland basin to areas uplifted during the Musgrave Orogeny.