Reviewerly/exHarmony huggingface dataset:
Attention-based machine vision models and techniques for solar wind speed forecasting using solar EUV images

Earth and Space Science Open Archive This work has been accepted for publication in Space Weather. Version of RecordESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing the latest version by default [v1]Attention-based machine vision models and techniques for solar wind speed forecasting using solar EUV imagesAuthorsEdward E. J.BrowniDFilipSvobodaiDNigel P.MeredithiDNicholasLaneRichard B.HorneiDSee all authors Edward E. J. BrowniDCorresponding Author• Submitting AuthorUniversity of CambridgeBritish Antarctic SurveyiDhttps://orcid.org/0000-0002-4719-9518view email addressThe email was not providedcopy email addressFilip SvobodaiDUniversity of CambridgeiDhttps://orcid.org/0000-0002-3183-6711view email addressThe email was not providedcopy email addressNigel P. MeredithiDBritish Antarctic SurveyiDhttps://orcid.org/0000-0001-5032-3463view email addressThe email was not providedcopy email addressNicholas LaneUniversity of Cambridgeview email addressThe email was not providedcopy email addressRichard B. HorneiDBritish Antarctic SurveyiDhttps://orcid.org/0000-0002-0412-6407view email addressThe email was not providedcopy email address
Plan S and the Quest for Global Open Access: March 2019 Edition

Plan S is an ambitious, EU-based effort attempting to accelerate the global tran- sition to open access. While this plan isnât the only one trying to improve open, or the first, it has generated much interest and discussion. Some in OSI support Plan S as written. Others support it with minor changes. Still others support the plan but with major changes, or the idea of Plan S but not this plan. As a body representing the views of all stakeholder groups in scholarly communication, the opinions and interests of OSI are broad. One of our goals, however, on Plan S and other issues, is to find common ground between these views. Therefore, this report provides a brief overview of Plan S, OSI's observations about it, and suggestions about where common ground might exist.
Breast cancer detection in ultrasound imaging

Breast cancer has become one of the most cancers among women in worldwide countries, as well as a leading cause of death. The use of ultrasound images in medical diagnosis and treatment of patients is critical. The success of cancer treatment and outcome is largely dependent on early detection. Imaging modalities such as ultrasonography are used to identify cancer. Ultrasound imaging is noninvasive, widely available, simple to use, and less expensive than other imaging technologies. As a result, ultrasonography is becoming more used as a cancer detection tool. Ultrasound imaging, on the other hand, is prone to noise and speckle artifacts. First, the ultrasound machine's raw picture data extraction is disabled. As a result, the process of recognizing malignant spots is prioritized. Artificial neural networks and other tissue characterization approaches are used. This technique was chosen because categorization and detection systems have greatly increased in their ability to assist medical experts in diagnosis. Manually classifying ultrasound images not only takes a long time and effort. As a result, a neural network classification-based automatic tissue characterization technique is proposed. Finally, the newly developed algorithms can aid specialists in recognizing suspicious aberrant tissue locations.
Role of Social Media on Buying Behaviour in Life Insurance Industry

This study seeks to investigate the power and role of social media with respect to Indian context relating to insurance industry. In this era of social media, new dimensions are being created every day. The widespread penetration of the Internet, its scope of use is increasing daily.Brands have made their imprint on these platforms, and social media has become a vital aspect of everyday life. Insurance firms have also gotten their fair share of social media attention. The focus now is on re-energizing their online presence, making it more engaging for customers and profitable for the company. When it comes to their social media strategy, insurers have acknowledged the necessity to innovate and optimize.The goal of this research is to examine the current condition of social media usage and its impact on the Indian insurance business.No one can deny the necessity of engaging with social media for analytics, to form opinions, draw conclusions, and reach better decisions. However, the conservative nature of the insurance industry has been a significant factor in the delayed adoption of social media.Our latest data show that there are 4.48 billion social media users around the world in July 2021, equating to almost 57 percent of the total global population. These figures suggest that more than 9 in 10 internet users now use social media each month Social media user numbers have surged in the past 12 months too, with 520 million new users joining social media in the year to July 2021.The present paper aims to define the forms and characteristics of social media as a soft power for people belonging to insurance industry in India.
Designing a Learning Model for an Artificial Intelligence Curriculum

AbstractThis study designed AI (Artificial Intelligence) learning model to effectively apply AI curriculum to culturaleducation in universities focusing on learners who perform AI education that is required in thecontemporary society for the upcoming 4th industrial revolution. The learning model diagnoses difficulties,personal levels and problems of learners in individual learning curriculum to recommend customized AIeducational contents that match with their capabilities by an intelligent decision-making system. Thus,this study provides assistance for their effective learning through AI learning model to enhance the qualityof educational environments.
Human Resource Aspect in Digital Library Era

Abstract: Information Communication Technology abbreviated as ICT, is undergoing latest advancement. Library and information professionals need to adopt these changes by enhancing their skills and knowledge to meet the user’s needs. This can be possible by learning and implementing new ICT skills and knowledge through training &amp; development, participating in conferences, seminar, workshop, self learning or any other medical of learning. Now the librarian in this digital era has to be proactive in implementing new tools and technological advancement in the library. This present article focuses the roles and functions of a librarian in this digital era, including information retrieval, navigation and browsing. This paper also summaries the skills, proficiencies, ability and competencies about professional and technological aspects that library professional staff should possess in order to meet the current and future needs of users. It will also help them to not only to survive in a rapidly changing technological environment but also enhance their professional and personal development. Keywords: Human Resource Development, Digital Library, Training and Development, Digital Competencies, Agencies of HRD, Information and Communication Technology (ICT)
Semantic Structural and Occlusive Feature Fusion for Pedestrian Detection

Pedestrian detection under occlusion scenes remains a formidable challenge in computer vision. Recently, anchor-free approach has been raised on the object detection and pedestrian detection field, anchor-free detector Center and Scale Prediction (CSP) has been proposed in pedestrian detection without special measures for occlusion. In this paper, we propose an anchor-free detector named OCSP with power ful occlusion handling ability to existing anchor-free detection network. OCSP integrates prior information into the network to handle occlusion. This high-fusion prior information gives the detector a hint about identifying the structural features of pedestrians. OCSP becomes more robust with the prior information which fusion the semantic head, the visible part, and the size and center body for each pedestrian. The detector enhances the perception of occlusion by predicting the semantic head and visible part. Besides, we design a head branch and add predicting the visible box to achieve a similar result. Experiments show that this fusion of prior information represents a suitable combination. We compare our OCSP with state-of-arts models on the Citypersons dataset, the proposed OCSP detector achieves the state-of-arts result on the CityPersons benchmark.
Large-Capacity Image Data Hiding based on Table Look-up

Abstract In previous data hiding techniques, binary rules are usually used to guide the fine-tuning of the values of basic objects in the host media to hide bit 0 and bit 1. In this paper, we propose a new data hiding technique for gray images based on querying a 256x256 information table. The information table is constructed by cloning a 3x3 basic block, which we call seed block. Eight unsigned integer values between 0 and 7, i.e ., 3 bit binary data, are assigned to different elements of the seed block. Each time, a pair of pixels are chosen from a host image, and their pixel values are used as row and column numbers to look up the information table. If element value obtained by looking up the table is equal to the 3 bit binary data to be hidden, the values of the pixel pair will remain unchanged. Otherwise, take this element as the central point, we call it the focus element, to enclose a 3x3 window in the information table. Then in the window, find the element which is equal to the data to be hidden. Finally, update the pixel values of the pair with the row and column numbers of the found element in the window. Since the row and column numbers are in the range of 0-255, the updated pixel values will not overflow. In the proposed algorithm, a pair of pixels can hide 3 bits of information, so the embedding capacity is very high. Since the adjustment of pixel values is constrained in a 3x3 window, the modification amount of pixel values is small. The proposed technique belongs to fragile digital watermarking, so it can be used for image authentication and tamper localization. By the evaluation of data hiding capacity, security, imperceptibility, computational cost and extensibility, this algorithm is superior to existing information hiding techniques. The proposed technique can also be used in color image and audio data hiding.
The Australian Covidsafe App and Privacy: Lessons for the Future of Privacy Regulation

This chapter provides a preliminary assessment of the Australian expe­rience with privacy regulation during the pandemic. It examines the Australian legislation enabling the introduction of the COVIDSafe app, before exploring the interac­tion between high levels of privacy protection and the generation of public trust. We argue that the need for specific rules dealing with COVIDSafe contact data has highlighted weaknesses in the Australia’s existing data protection framework under the Privacy Act. The chapter also considers the privacy issues arising from digital visitor registration at public venues for contact tracing and analyses the effect of recent public debates about privacy for the future of privacy regulation in Australia. In our view, the public discourse about data protection during the pandemic demonstrates that Australians attribute high value to their privacy, even in a time of crisis. The example of the COVIDSafe app illustrates that robust privacy protections are critical to achieving a strong community uptake of new data-driven technologies. We submit that Australian society would therefore benefit if the government gave better recognition to privacy interests, and their protec­tion, than it has done in the past.
Diagnosing Errors in Video Relation Detectors

Video relation detection forms a new and challenging problem in computer vision, where subjects and objects need to be localized spatio-temporally and a predicate label needs to be assigned if and only if there is an interaction between the two. Despite recent progress in video relation detection, overall performance is still marginal and it remains unclear what the key factors are towards solving the problem. Following examples set in the object detection and action localization literature, we perform a deep dive into the error diagnosis of current video relation detection approaches. We introduce a diagnostic tool for analyzing the sources of detection errors. Our tool evaluates and compares current approaches beyond the single scalar metric of mean Average Precision by defining different error types specific to video relation detection, used for false positive analyses. Moreover, we examine different factors of influence on the performance in a false negative analysis, including relation length, number of subject/object/predicate instances, and subject/object size. Finally, we present the effect on video relation performance when considering an oracle fix for each error type. On two video relation benchmarks, we show where current approaches excel and fall short, allowing us to pinpoint the most important future directions in the field. The tool is available at \url{https://github.com/shanshuo/DiagnoseVRD}.
“BeDiL” Learning Media Training in The New Normality Era

Online learning is a new phenomenon for educators. This requires education actors, such as educators, education staff, governments, students, and even parents of students to be able to work together in building interactive learning. Online learning is a learning method/way that can motivate students to learn more and achieve learning objectives. However, not all educators can adapt quickly, especially for educators who work in the field at the front lines. This can happen because, over the years, educators have been accustomed to face-to-face or offline teaching models instead of a virtually face-to-face or online model. When learning is carried out online, this becomes a challenge for educators where they have to learn many new things such as the media platforms, new presentation methods, or adapted teaching strategies so that learning can be done effectively. Moreover, an educator is a wheel in learning. Therefore, training on the design of a learning media, especially in the face of this new normal era, is crucial to do. This training activity is carried out using the learning-by-doing method. This method was chosen because the training activities were carried out in a guided manner. Based on the training activities two results can be obtained. First, the training related to the BeDiL learning media has been carried out smoothly. Second, participants can make BeDiL learning media in the form of posters that can be classified into two, namely complete BeDiL posters and incomplete BeDiL posters.
High-Performance RNS Modular Exponentiation by Sum-Residue Reduction

Abstract Modular exponentiation is fundamental in computer arithmetic and is widely applied in cryptography such as ElGamal cryptography, Diffie-Hellman key exchange protocol, and RSA cryptography. Implementation of modular exponentiation in residue number system leads to high parallelism in computation, and has been applied in many hardware architectures. While most RNS based architectures utilizes RNS Montgomery algorithm with two residue number systems, the recent modular multiplication algorithm with sum-residues performs modular reduction in only one residue number system with about the same parallelism. In this work, it is shown that high-performance modular exponentiation and RSA cryptography can be implemented in RNS. Both the algorithm and architecture are improved to achieve high performance with extra area overheads, where a 1024-bit modular exponentiation can be completed in 0.567 ms in Xilinx XC6VLX195t-3 platform, costing 26,489 slices, 87,357 LUTs, 363 dedicated multipilers of $18\times 18$ bits, and 65 Block RAMs.
Comparision of two sentiment analysis algorythms

This paper presents the comparison of the capabilities of two algorithms for Sentiment Analysis developed in Python. Both Python programs are used on the same Yelp dataset with customer reviews of the quality of the services in USA restaurants. The programs are based on open-source software frameworks and libraries as Python, NTLK, Scikit-Learn, Panda, etc. which are oriented to Machine and Learning and Natural Language Processing. The evaluation of the programs is based on precision of the predicted results and the compactness of the programming code. For model training and prediction, the Multinomial Naive Bayes and Support Vectors Machines classifiers are applied in both algorithms.
Implementation of Face Recognition by using of Decision Tree and PART Algorithms Based on LDA

Face recognition is one branch of pattern recognition that has become an important subject in modern life, as surveillance and security applications. So, face detection and recognition have gotten a lot of interest from computer vision and image processing technologies. This paper proposed a new face recognition method by use of the two classifier algorithms of J48 decision tree and PART (partial decision tree) algorithms for classifier human faces combined with linear discriminant analysis (LDA) algorithm to solve the problem of complexity of classifier of the colour images, that by use of LDA to the extraction of face feature and reduction of data dimension of the image from 2D to 1D feature vector before classifier. MUCT database consisted of 3755 colour images of person is pre-processing and extracted of features by LDA, these features are split into70% for training and 30% for testing of classifiers to the computation of performance of face recognition system. The results showed that the evaluation performance of the PART algorithm is better than the J48 decision tree for the classified face image in face recognition tasks. That the precision, recall, and F-measure of the PART algorithm are 96.99, 96.84, and 96.83 respectively, whereas J48 decision tree methods are 96.60, 96.445, and 96.44 respectively.
Application of Mind Mapping Learning Models to Improve Students’ Reading Skill in 4th Grade of Primary School

Data showed the existence of problems found in 4th grade during Indonesian Language learning in reading comprehension material. Reading comprehension aims to obtain information from the text. Problems are found in two important aspects of learning; teacher performance and student activities. The discovery of the problem is because the teacher uses a learning method that makes students less enthusiastic when delivering learning material. For this reason, classroom action research was conducted using a spiral model from Kemmis and Taggart. The corrective action taken is to apply the mind mapping learning model. Mind mapping is designed to help students to easily remember and understand the information that contained in the text. Preliminary data explained that 9 students completed learning or 33.33% of 27 students. The action is carried out in two cycles. It is because new targets are reached in the second cycle. From the results, we can concluded that mind mapping is able to improve student learning outcomes in reading material understanding in Indonesian language learning
Experiencia primaria sobre la virtualización en los estudios generales de la carrera de Turismo en la UCSG, Ecuador

An adequate perspective is offered on the impact of information and communication technologies in Higher Education and, especially, about virtualization, as a space in which the need for scientific analysis is established based on its use and development in the way required by the present. This study responds to a non-experimental descriptive research logic, with a mixed methodological approach. It is, fundamentally, the configuration of a theoretical-methodological conception to favor virtualization, with its respective implementation procedure, which constituted an alternative scientifically based and articulated from the methodological point of view. The results denote the integration in a systemic way regarding the legal, organizational, communicative, pedagogical and technological dimensions, depending on the virtualization process with a necessary, pertinent and effective character, in correspondence with the possibilities and potential of the UCSG. In this sense, it was evidenced that the concept favors the adaptation of teachers and students to the virtual environment and the use of digital resources and tools in this regard.
A COMPARISON OF CREATING AN ANDROID APPLICATION USER INTERFACE IN XAML AND IN C# CODE

Almost every Android user application has some kind of user interface. Android programmers who create Xamarin.Forms applications and who uses the Microsoft Visual Studio development environment to do so can create user interfaces in the XAML (the Extensible Application Markup Language) or in the C# programming language. This paper deals with a comparison of creating this user interface by the first and the second way. We demonstrate the differences in the creation of Android application user interfaces in XAML and in C# by way of using two of our Android applications which were created by the Microsoft Visual Studio 2019 Enterprise, which work as text editors with the ability to store text to disc, and have user interfaces that are visually identical. However, the user interface of the first Android application was created in XAML with a C# support code, whereas the user interface of the second Android application was created entirely in C#. While comparing the source codes of the user interfaces of both these Android applications, we identify the advantages and disadvantages of both approaches to creating a user interface and we try to find out which of these approaches is better for maintaining and modifying user interfaces. In this study, we also contrast the processes of handling events of controls of a user interface created in the XAML code for the first Android application as well as that of the same user interface created in the C# code for the second Android application. Furthermore, we were interested in determining whether the different ways of creating user interfaces affected the execution time of basic operations that included disc files that were performed on the same data by both the applications. We assume that it does not fundamentally affect the execution time, and so, we performed an experiment to confirm or refute our assumption.
Scientific substantiation of the role of choreographic art in the cultural process

The work shows that the purpose of choreographic art is to convey to a significant part of listeners the imageries, thoughts and the formation of views that become the basis for the growth of cultural perception. Choreographic art is understood by the authors of the article as part of a single process of human cultural development. The article reveals successively the technology of the formation of the choreographic process as part of the socio-cultural exchange, as well as an aspect of the formation of prerequisites for the personal growth of an individual who becomes a participant in cultural exchange. The authors showed that the use of choreographic art is understood not only as a visualized part of the basic artwork of a text plan, an artistic one, but it can also act as an object of knowledge as an independent unit. The novelty of the article is the position that the use of choreographic art as part of cultural exchange is based on the psychological perception of the individual to the cultural process.
Library Research Guides: Image Resources: Open Access Images

This guide contains image resources available through IU Libraries (both campus specific and university-wide) as well as information about open access images.