Reviewerly/exHarmony huggingface dataset:
Semi-supervised labelling of chest x-ray images using unsupervised clustering for ground-truth generation

Supervised classifiers require a lot of data with accurate labels to learn to recognize chest X-ray images (CXR). However, manually labeling an extensive collection of CXR images is time-consuming and costly. To address this issue, a method for the semi-supervised labelling of extensive collections of CXR images is proposed leveraging unsupervised clustering with minimum expert knowledge to generate ground truth images. The proposed methodology entails: using unsupervised clustering techniques such as K-Means and Self-Organizing Maps. Second, the images are fed to five different feature vectors to utilize the potential differences between features to their full advantage. Third, each data point gets the label of the cluster’s center to which it belongs. Finally, a majority vote is used to decide the ground truth image. The number of clusters created by the method chosen strictly limits the amount of human involvement. To evaluate the effectiveness of the proposed method, experiments were conducted on two publicly available CXR datasets, namely VinDR-CXR and Montgomery datasets. The experiments showed that, for a KNN classifier, manually labeling only 1% (VinDr-CXR), or 10% (Montgomery) of the training data, gives a similar performance as labeling the whole dataset. The proposed methodology efficiently generates ground-truth images from publicly available CXR datasets. To our knowledge, this is the first study to use the VinDr-CXR and Montgomery datasets for ground truth image generation. Extensive experimental analysis using machine learning and statistical techniques shows that the proposed methodology efficiently generates ground truth images from CXR datasets.
KAJIAN EFEKTIFITAS GULLY PLUG DALAM PENGENDALIAN RUN OFF DI KAWASAN HULU DAS PULISAN

The flood problem in Pulisan village that occurred in 2019 is one of the problems that needs to be addressed immediately because it causes losses to residents living around the river, and disrupts vehicle traffic. One of the causes of flooding in the Pulisan river is the magnitude of the run off and the large flow rate so that potential flooding events can occur. Therefore, run-off control is needed in the upstream area of the Pulisan river. Pulisan watershed has a total watershed area of 3.25 km2 and has 9 tributary channels. The location reviewed is in the Pulisan river channel with selected sections is the channel of 5 Pulisan rivers which has a watershed area of 0.2512 Km2. The Araren-Pigrandma MRG rain post and the Maen Climatology rain post are sources of maximum daily rainfall data used with a time span of 2002 to 2021. HEC-HMS software is used to obtain the parameters needed to obtain a peak discharge of 2.2 m3 / second and a planned flood discharge. HEC-RAS software to analyze water level and flow rate when using gully plug. The simulation results show that from several types of gully plugs, a significant reduction in flow speed is in type 60 gully plugs, namely the flow speed to 0.6 – 1 m / second, the flow speed does not cause deposits in the channel.
ANALISIS PEMANFAATAN VIDEO PEMBELAJARAN DALAM MENINGKATKAN HASIL BELAJAR PADA PELAJARAN EKONOMI DI KELAS X IIS SMAN 1 JAWAI SELATAN

ABSTRAKThis study aims to determine how to use school facilities. Those who are at school are to make learning media as good as possible at school. And learning media to attract students' attention so they don't get bored in class. Researchers use video media as a learning medium. To provide enthusiasm and motivation for students. So that you don't get bored studying in class. Video media helps researchers to attract the attention of students to return to focus on the researchers and the material presented by the researchers. the use of Video in Economics learning in Class X IIS SMAN 1 Jawai Selatan with the use of school facilities to find out how the use of video is carried out at SMAN 1 Jawai Selatan School by researchers who are carried out in schools. Student Learning Outcomes in Economics learning in Class X IIS SMAN 1 Jawai Selatan. The learning videos that are displayed are not too long and not boring. By using learning video media, students find it easier to learn in class and it is not boring for students what researchers do at school. The use of video in improving learning outcomes in Economics lessons in Class X IIS SMAN 1 Jawai Selatan. before showing the learning video, the researcher explained the material first to the students. After seeing the students getting bored, then the researcher displays the media that has been prepared by the researcher, namely video media. To improve student learning outcomes at SMAN 1 Jawai Selatan.Keywords Improving Learning Outcomes, Learning Videos, and Utilization
An Automatic Collision Avoidance with Disturbance Interval Observer for Unmanned Aerial Vehicle

An automatic collision avoidance with disturbance interval observer (DIOB) for unmanned aerial vehicle (UAV) in non-cooperative uncertain environments is proposed in this paper. First, the collision detection condition and the linear time-varying collision avoidance model based on the collision cone are given. And, the anti-disturbance control law with DIOB is designed to ensure the safety of UAV collision avoidance. Then, the stability of the UAV collision avoidance control system with DIOB is proved through the Lyapunov theory. The simulation results demonstrate that the proposed method can achieve UAV automatic collision avoidance in unknown obstacle acceleration.
Earthquake early warning in Central America: The societal perspective

Central America has an elevated seismic risk, resulting from the vulnerability of the building stock and steady population growth. Earthquake Early Warning (EEW) aims to provide warning in advance of imminent shaking, allowing recipients to take action and reduce casualties during damaging motions. The Swiss Seismological Service (SED) has been collaborating with local seismic agencies to develop national EEW systems across Central America, which can potentially benefit nearly 47 million inhabitants. We conducted a public survey to comprehend the desire for EEW, the preferences for EEW attributes, and the current behaviour of people during earthquakes and the driving factors behind it. We recruited participants from Nicaragua (N = 513), Costa Rica (N = 1350), Guatemala (N = 559), and El Salvador (N = 491). In all four countries, participants consider it necessary to have an EEW system, are tolerant of false alerts, and are likely to react promptly to alerts. The desirable alert threshold is for low felt intensities, ranging between MMI III to IV. We found that a significant number of respondents already take protective action when earthquakes strike, and appropriate reactions are expected to increase when EEW is available. Our survey is unique in providing insights into the social dimension of EEW systems in low-income regions with high earthquake risk and where no operational EEW system yet exists.
De-Centralized Identity Management For Virtualized Healthcare

&nbsp; The annual ConV2X is a leading international health tech symposium driving real world evidence, strategy, research, operations and trends to create a blueprint for a new digital health era. The 2021 symposium&nbsp;featured a scientific program of academic/research presentations in addition to business and industry talks. The research track&nbsp;focused on exploring and sharing developments in blockchain and emerging technologies in health and clinical medicine. Submissions were based on original research, conceptual frameworks, proposed applications, position papers, case studies, and real-world implementation. Selection was based on a peer-review process. Faculty, students, and industry researchers were encouraged to submit abstracts to present&nbsp;ideas before an informed and knowledgeable audience of industry leaders, policy makers, funders, and researchers. This presentation was selected by the scientific review committee. Submission Review Committee Dave Kochalko, CEO of ARTiFACTS Anjum Khurshid, UT Austin Carlos Caldas, UT Engineering Gil Alterovitz, Harvard Medical School Kayo Fujimoto, UT Health Houston Lei Zhang, University of Glasglow Sean Manion, CSciO of ConsenSys Health Vijayakuman Varadarajan, University of South Wales Vikram Dhillon, Wayne State University Yuichi Ikeda, Kyoto University &nbsp
Applications for Interfaces

In this chapter, we will discuss some interesting applications of interfaces in Java and how they relate to Go coding.
Key Method/Function Comparison

This chapter describes many Go packages and the types in them and the functions they provide. Some examples are also provided.
Blockchain-Based Healthcare Monitoring System Using Patient Electronic Health Record

The majority of hospitals and other healthcare institutions have made the switch from paper-based techniques to something that is known as electronic health records, or EHRs. This change was made possible by technological advancements. Various parties need to exchange the data records they keep on one another, and users need to be allowed to exercise control over who has access to the information they have on file. The Electronic Health Record (EHR) system is beset by issues relating to managing problems, challenges with trust, and data protection. Data stored on blockchains are immutable, private, and accessible only by their intended users. Blockchain technology's use has also led to managing a system with the potential to provide decentralized data storage. In this research, we determine whether it is appropriate to deploy blockchain technology in EHR and explore its potential uses in the efficient leadership of the COVID-19 pandemic.&#x0D;
How the Covid-19 Pandemic Magnifies Existing Urban-Rural Educational Inequality in China

Through analyzing past essays on educational inequality, our group finds that such inequality is established very early and deep in Chinese society. The most crucial cause of urban-rural inequality is the family background an extreme intergenerational inequality based on parents' educational level and family wealth. Other causes include technological differences and employment patterns. After identifying the causes, our group examines the influence of the pandemic on rural-urban inequality, and the result points out that covid elongates the gap. Furthermore, the financial capability of rural families is worsened under the covid since lots of small businesses owned by rural families shut down because the lockdown depleted their cash flows. Additionally, technology, which is very rare in rural areas compared to cities, has become vitally crucial under the context of Covid.
MOTIVATION AND INTEREST: DOES IT HAVE AN INFLUENCE ON PJOK LEARNING OUTCOMES IN ELEMENTARY SCHOOL CHILDREN?

Learning outcomes have an important role in the learning process. This is because learning outcomes can be used as a benchmark to find out how far changes in students after receiving their learning experience can be observed and measured in the form of knowledge, attitudes, and skills. This study aims to determine whether there is an influence of motivation to learn and interest in learning on the learning outcomes of PJOK subjects. This study uses a type of correlational research with multiple regression techniques. This research was conducted at SDN 4 Dauhwaru with a total sample of 30 people consisting of 15 students and 15 female students. Data collection techniques for the level of motivation and interest in learning in this study used a questionnaire while the learning outcomes used skill scores in PJOK subjects. The results of this study are that motivation and interest in learning have a positive influence on learning outcomes in PJOK subjects.
Metaverse, the last technological frontier of environmental sustainable food: Worldwide evidence from the first business case studies

The purpose of this paper is to highlight for the first time the potential offered by this innovative technological opportunity in the coming years. The metaverse probably represents the boundary between the most avant-garde current innova-tions and, at the same time, what could be the possible development potentials of the near future. Through considerations on current knowledge and, above all, with the help of empirical evidence from the first business cases of metaverse applica-tions in the food sector, it is possible to understand how food companies can win in increasingly fierce international competition; it is necessary to invest more and more in economically, socially and environmentally sustainable strategic actions, above all in really new technological innovations. From the analysis of the first ex-isting case studies it is clear that the metaverse is certainly an innovation that opens up new sustainable economic possibilities, also for companies in the food sector. To date there are no other studies like this on this topic and, in particular, in the food system. However it is only a starting point for further future studies. Yet, it is already possible to identify the strategic potential of the metaverse.
Educational Innovation in Teacher Classrooms

The teaching paradigm is undergoing a real revolution in addition the pandemic situation suffered from COVID-19. Therefore, both teachers and faculty must adapt and train so as to give an adequate response that improves the results and favors the motivation for learning. They are putting their focus on the permanent training of teachers and on educational innovation. One of the most current and innovative teaching innovation tools is gamification. Therefore, this study aims to analyze the existing scientific literature, carrying out a systematic review of the empirical studies that show experiences carried out in university classrooms, especially in careers related to teaching in different specialties. Discarding the texts that did not meet the eligibility criteria, six articles were selected that are committed to teaching innovation and the practice of educational strategies such as gamification in university classrooms to promote meaningful learning as well as the involvement and motivation of students towards learning.
Online Learning in Times of Pandemic

The present study deals with a systematic review on virtual education in higher education during the COVID-19 health crisis to know the digital competence of teachers and student perception of online learning. The scientific literature was analyzed during the years 2020-2022 based on empirical and theoretical studies in the Spanish university environment. The results show a certain weakness of telematic teaching with respect to face-to-face teaching. Technology is a powerful tool that requires planning, an aspect that was not adequately developed in times of pandemic. COVID-19 has revealed technological deficiencies in teachers, which implies that we are still developing in the digital framework and their use is reduced to the minimum expression of all the potential they have. In general, university students feel satisfied with virtual teaching. They have recognized the potential that ICT has in the “learning to learn” competition, but have emphasized an increase in academic stress, backed by the psychological impact of confinement.
Asymptotic Edge of Chaos as Guiding Principle for Neural Network Training

It has been recently demonstrated that optimal neural networks operate near the asymptotic edge of chaos for state-of-the-art feed-forward neural networks, where its generalization power is maximal due to the highest number of asymptotic metastable states. However, how to leverage this principle to improve the model training process remains open. Here, by mapping the model evolution during training to the phase diagram in the classic analytic result of Sherrington–Kirkpatrick model in spin glasses, we illustrate on a simple neural network model that one can provide principled training of the network without manually tuning the training hyper-parameters. In particular, we provide a semi-analytical method to set the optimal weight decay strength, such that the model will converge toward the edge of chaos during training. Consequently, such hyper-parameter setting leads the model to achieve the highest test accuracy. Another benefit for restricting the model at the edge of chaos is its robustness against the common practical problem of label noise, as we find that it automatically avoids fitting the shuffled labels in the training samples while maintaining good fitting to the correct labels, providing simple means of achieving good performance on noisy labels without any additional treatment.
Attention-based dual-color space fusion network for low-light image enhancement

The low visibility and dull colors associated with low-light images are not only difficult to satisfy the photographer, but also hinder further visual tasks. In this study, we propose an attention-based dual-color space fusion network to enhance low-light images. By introducing HSV color space, the network can solve the problems of dim color and insufficient contrast existing in previous RGB color space methods. In both color spaces, the network adopts a large number of attention mechanisms to highlight important features in real time. To better achieve feature fusion across color space, we design adaptive large-kernel attention (ALKA) and feature extraction module (FEM), respectively. The ALKA adaptively selects features for enriching the encoding input in the HSV color space during the RGB color space encoding process. The FEM assists the network in more comprehensive supervision of the enhancement process and generates the attention map to transmit the marking features in the previous color space. At the end of the network, we also design channel enhancement module (CEM) to protect the texture details lost during the scale change. We have conducted experiments on a variety of public datasets, and both subjective and objective comparisons have demonstrated the particularity and prominence of our method.
Three Dimensional X-ray CT Reading Assistance System with Video See Through Display

In recent years, the amount of information in three-dimensional X-ray Computed Tomography (3D X-ray CT) has been increasing, and research on Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) representations using computer graphics rendering has progressed. Conventionally, medical professionals have used Digital Imaging and Communications in Medicine (DICOM) viewer software to display data captured with 3D X-ray CT in three directions (axial, sagittal, and coronal section) on a PC monitor. Since surface and volume rendering on AR, VR, and MR is primarily used, making it is difficult for the observer to accurately represent the region of interest. In our previous research, a 3D expression system that 2D cross-section images output from DICOM on the surface-rendered object has been proposed. In this study, a representation method using a 3D expression system and showing AR images allows the user to check the internal structure of an object imaged by 3D X-ray CT in any position and rotation has been newly proposed. In addition, in order to express a cross-section of a virtual object at close range in real-time, HTC VIVE Pro, which is a camera-mounted device connected to a PC, enabled a video see-through expression. As a result, a 3D X-ray CT reading assistance system enabled the user to confirm the internal structure of a specific part of a CT-imaged object in a virtual reality space while maintaining shading and a three-dimensional impression.
Surveyor’s manual on the online application of the “NOVA 27 UPF Categories Tracker” and the “24-hour reminder” survey, multi-step method

This manual was created to train the surveyors who will be in charge of applying the electronic versions of the “NOVA 27 UPF Categories Tracker” and the “24-hour reminder multi-step method” questionnaires.
Inconsistent measurement and incorrect detection of software names in security vulnerability reports

As the number of vulnerability databases established by various nations continues to grow, they have accumulated hundreds of thousands of security vulnerability reports, which play a crucial role in protecting system security. However, many databases are found to lack essential information, contain inaccuracies, or are inconsistent with others. Despite these challenges, the importance of vulnerability databases continues to grow. Current research on vulnerability databases is limited to software version and vulnerability reproduction, but the software names, an essential component of vulnerability databases, have not been extensively studied. Understanding the consistency of software names in different vulnerability databases is crucial for improving the accuracy of vulnerability databases. The paper introduces VERNIER, an automated method for measuring inconsistencies in 789,954 sets of software names from nine security vulnerability databases (including CVE and NVD) from 1999 to 2019. We utilized a named entity recognition (NER) model with exceptional accuracy (99.5%) and F1 score (95.1%) to extract software names from unstructured Chinese and English vulnerability reports. VERNIER assesses software names' inconsistency at character and semantic levels. The results indicate that inconsistent software names are prevalent in vulnerability databases. The average of the exact matching rate between NVD and other mainstream databases, such as CVE, is only 20.3% at the character-level and 43.3% at the semantic-level. We also discover internal inconsistencies between the structured and unstructured software names inside the same vulnerability database (e.g., NVD). To mitigate the inconsistency, we implement an alert tool using inconsistencies to detect incorrect software names. This tool can effectively warn and correct software names.
The Practice, Theoretical Disputes and Judicial Embeddedness of the of Blatant Theft

There is no final conclusion about whether theft adheres to “secret theft” or compatible with “blatant theft” in terms of objective behavior. Although traditional theories occupy the main position in judicial practice, there have been judgments that agree with the theory of “blatant theft”. Through the analysis of cases that adopt the theory of “blatant theft” in judicial practice, this paper examines the specific problems faced by the theory of blatant theft in the application of judicial practice. After that, this paper further demonstrates the rationality of embedding the blatant theft theory into judicial practice, and puts forward the specific approach of embedding this theory into judicial practice.
Research on the Construction of Remixed Creative Rights in China in the Remixed Era

With the development of digital network technology, the public’s ability to use, create, and disseminate works has further enhanced. Digital network technology has brought new means and methods to obtain works, and has further triggered the phenomenon of remixing culture where creators recombine existing works such as text, music, and videos to create new works. While promoting cultural diversity, remixed works have also raised many copyright issues. Currently, China’s copyright law does not explicitly regulate remixed behavior, which is not conducive to protecting the creative enthusiasm of remixed creators. Therefore, this paper analyzes the shortcomings of existing copyright protection from specific judicial cases, and attempts to propose suggestions such as incorporating remixed works into the scope of copyright law protection, establishing remixed creation rights for remixed creators, and introducing knowledge sharing agreements. A legal system suitable for remixed creation should be constructed in order to balance the benefit sharing between rights holders and users.