Reviewerly/exHarmony huggingface dataset:
Interactive Learning Media using Adobe Animate CC to Improve Students’ Learning Motivation and Mathematics Learning Outcomes

This study aims to apply digital learning media in the form of Adobe Animate CC in learning mathematics. This research is a quantitative research with a comparative approach to compare learning outcomes based on the application of interactive learning media Adobe Animate CC. The research population was all junior high schools in Bengkalis Regency, while the sample was a portion of the schools taken purposively according to the purpose of the research. The data collection tool is a learning achievement test and a checklist to observe student learning motivation in class while studying with Adobe Animate CC. Data analysis in this study used descriptive statistics, t-test and One Way Anova. The results of the analysis show that there are significant differences in student learning outcomes in the experimental class using Adobe Animate CC learning media and the control class using conventional learning. There were significant differences in learning motivation in the experimental class at the first meeting, second meeting, third meeting and fourth meeting. Adobe Animate CC learning media can improve learning outcomes and motivation of junior high school students in Bengkalis Regency, Riau Province. Keywords: digital learning media, learning outcomes, learning motivation. Abstrak: Penelitian ini bertujuan untuk menerapkan media pembelajaran digital berupa Adobe Animate CC dalam pembelajaran matematika. Penelitian ini merupakan penelitian kuantitatif dengan pendekatan komparasi untuk membandingkan hasil belajar berdasarkan penerapan media pembelajaran interaktif Adobe Animate CC. Populasi penelitian adalah seluruh sekolah menengah pertama di Kabupaten Bengkalis sedangkan sampel adalah sebagian sekolah yang diambil secara purposive sesuai dengan tujuan dilaksanakan penelitian. Alat pengumpulan data adalah dengan tes hasil belajar dan daftar checklist untuk mengamati motvasi belajar siswa di kelas selama belajar dengan Adobe Animate CC. Analisis data dalam penelitian ini menggunakan statistik deskriptif, t-test dan One Way Anova. Hasil analisis menunjukkan bahwa terdapat perbedaan signifikan hasil belajar siswa pada kelas eksperimen menggunakan media pembelajaran Adobe Animate CC dengan kelas kontrol menggunakan pembelajaran konvensional. Terdapat perbedaan signifikan motivasi belajar pada kelas eksperimen pada pertemuan pertema, pertemuan kedua, pertemuan ketiga dan pertemuan keempat. Media pembelajaran Adobe Animate CC dapat meningkatkan hasil belajar dan motivasi siswa sekolah menengah pertama di Kabupaten Bengkalis Provinsi Riau. Kata kunci: media pembelajaran digital, hasil belajar, motivasi belajar. DOI: http://dx.doi.org/10.23960/jpmipa/v24i1.pp172-182
Policing of the Far-Right Online: The Cases of the UK and Hungary

Far-right groups have increasingly been able use and weaponize the online space for activism, especially in regard to create radicalizing effects that lead to political violence. This article explores how policing communities are treating far-right groups online, what strategies they’ve been using, and the effect this has on far-right activism. Using interviews with practitioners and key in-depth case studies of far-right groups in the U.K. and Hungary, what it finds overall is that policing communities are increasingly using more sophisticated tactics to combat far-right content. In the future, this research advocates for more transparency about tactics and reasoning behind policing strategies used in the online space.
Phase estimation of a Mach-Zehnder interferometer via the Laguerre excitation squeezed state

Quantum metrology has an important role in the fields of quantum optics and quantum information processing. Here we introduce a kind of non-Gaussian state, Laguerre excitation squeezed state as inputs of traditional Mach-Zehnder interferometer to examine phase estimation in realistic case. We consider the effects of both internal and external losses on phase estimation by using quantum Fisher information and parity detection. It is shown that the external loss presents a bigger effect than the internal one. The phase sensitivity and the quantum Fisher information can be improved by increasing the photon number and even surpass the ideal phase sensitivity by two-mode squeezed vacuum in a certain region of phase shift for realistic case. Our results can find significant practical applications in quantum metrology.
Touching with the eyes: Oculomotor self-touch induces illusory body ownership

[This corrects the article DOI: 10.1016/j.isci.2023.106180.].
Capsule-Based Regression Tracking via Background Inpainting

Background cues play an accompanying role in most regression trackers, where they directly learn a mapping from dense sampling to soft label by giving a search area. In essence, the trackers need to identify a large amount of background information (i.e., other objects and distractor objects) under the circumstance of extreme target-background data imbalance. Therefore, we believe that it is more worth performing regression tracking depending on the informative background cues and using target cues as supplementary. To do this, we propose a capsule-based approach, referred to as CapsuleBI, which performs regression tracking based on a background inpainting network and a target-aware network. The background inpainting network explores the background representations by restoring the region of the target with all available scenes, and a target-aware network captures the target representations by focusing on the target itself only. To explore the subjects/distractors in the whole scene, we propose a global-guided feature construction module, which helps enhance the local features with global information. Both the background and target are encoded in capsules, which can model the relationships between objects or object parts in the background scene. Apart from this, the target-aware network assists the background inpainting network with a novel background-target routing algorithm that guides the background and target capsules to estimate the target location with multi-video relationships information precisely. Extensive experimental results show that the proposed tracker achieves favorably against state-of-the-art methods.
Real-time musical performance across and within extended reality environments

The design of real-time digital musical instruments, both novel as well as the emulation of traditional musical performance practices using computer systems, has always required nearly imperceptible latencies between controlling gesture and expressed sound. Sound and music based experiences built within immersive visual rendered spaces often struggle to provide seamless articulate control of rendered dynamic output. Working across and within extended reality environments, the complexity of the challenge continues to evolve with current generations of hardware and software pushing core and graphics processors to their respective limits. The introduction of networked performance spaces has only added to the complexity, resulting in the need for additional latency mitigation strategies from both the technical and artistic domains. This paper will discuss recent creative and technical strategies and concerns in the design, development and use of real-time virtual musical instruments.
Pemanfaatan Platform Kahoot Sebagai Media Pembelajaran Interaktif

Conducive and enjoyable learning in the industrial revolution 4.0 makes a change in learning styles in the learning process. Teachers are required to follow an interactive digital learning process. Fun and non-boring learning is one of the challenges for instructors and Learning Technology Developers to innovate in learning. Interactive learning innovation in this study is to use Kahoot as an interactive learning media based on game based learning that emphasizes the active participation learning styles of all students. One of the Kahoot Platforms used was the use of online quizzes, where students immediately reflected their answers online and Kahoot recorded all the activities of students that could become assessment resume materials for teachers. This study aims to find out how the Kahoot application is feasible in the learning process by understanding students' responses to this application. This study uses a Qualitative method by using Kahoot in the learning of 22 students who take the Business Feasibility System course in the Faculty of Economics Study Program, Campus II Payakumbuh Andalas University. This study obtained a final percentage of 85% with Very Interesting criteria. It was concluded that the use of the Kahoot platform used was very suitable to be used in creating interactive and fun learning.Keywords: Industrial Revolution 4.0, Kahoot, Qualitative
ONLINE EXAMINATION SYSTEM USING CLOUD

The online Examination portal is a web-based application for technical evaluation.The online examination portal not only replaces paperwork but also releases the workload of faculty.Most of the e-examination (Online Examinations) has fixed number of questions without randomizations, they have pool scalability.Online examination system is increasing rapidly with the change in scenario due to the pandemic, also it seems to be an easy, flexible, and secure methodology to carry the examinations effectively.
EDGE INTELLIGENCE: ENABLING SMART AND COLLABORATIVE AI SYSTEMS AT THE EDGE

Edge intelligence, which leverages the computing power of edge devices to enhance the intelligence and decision-making capabilities of distributed AI systems, has emerged as a promising paradigm for developing smart and collaborative systems at the edge.This review paper provides an overview of the latest research and advancements in the field of edge intelligence, highlighting the potential benefits and challenges of using this approach for developing intelligent and collaborative systems at the edge.We discuss the techniques and algorithms that are being used to enable edge intelligence, including machine learning models that are specifically designed for edge devices, federated learning and decentralized learning techniques that allow edge devices to collaborate and share knowledge, and real-time edge analytics for AI.We also discuss the security and privacy challenges that arise in edge intelligence systems and propose some solutions to address them.Finally, we identify some open research problems and future directions for edge intelligence, including hybrid AI systems that combine cloud and edge computing, and edge-to-cloud orchestration for enhancing the performance and scalability of AI systems.
Clear speech in the new digital era: Speaking and listening clearly to voice-AI systems

It’s a new digital era: many people regularly talk to voice-activated artificially intelligent (AI) personal assistants, such as Siri, Alexa, and Google Assistant, that spontaneously and more naturalistically produce interactive speech. Human speech patterns toward these new voice-AI interlocutors can serve as a “Turing” test for discovering how people adapt their production and perception to improve communication during spoken language interactions. In this research program, we explore how interactions with voice-AI can influence human speech patterns during short-term interactions, and the potential that this has to lead to sound change within speech communities. In this talk I will present two case studies representing the types of studies we are conducting to explore how voice-AI interactions influence human speech patterns. First, we investigate how speakers adapt their speech when talking to devices, particularly to be better understood where the devices display comprehension difficulties. Second, we examine the intelligibility of text-to-speech (TTS) and how listeners can adapt their listening strategies during interactions with devices to better understand. Our work demonstrates that examining people’s speech behavior when interacting with voice-AI can serve as a test to our scientific understanding of speech communication, language use, and even linguistic change.
Acoustic effects of varying the waist width of violin bridges: A physical experiment

We explore the relationship between the bridge waist and sound production in the violin. Models of violin acoustics suggest that the stiffness of this portion of the bridge has a considerable effect on an instrument’s sound production. In practice, the proportions of the waist vary significantly from bridge to bridge and instrument to instrument, which suggests there are many ways that a luthier can influence a bridge’s stiffness. Our experiment connects modeling and real-world instrument sound adjustment. We incrementally remove material symmetrically from the bridge in the waist area, recording sound production at each increment. The bridges are destroyed in the process, which is repeated across multiple bridges. Sound stimuli include a sine wave at the bridge with dampened strings and a weighted bow drawn across freely ringing strings. We map changes in bridge geometry to changes in maximum output and acoustic measures of tone quality across several instruments. Since stiffness correlates with thickness, subject to the nature of the bridge material, there may be optimal shape adjustments for maximizing sound production, tone quality, or both.
Agent-oriented configuration of human-machine systems in the organization of scientific and technical activities in Russia and abroad in industries with high requirements for the reliability of technological processes

The article deals with the problems of using new digital services to organize the development and implementation of agent-individualized work trajectories of human-machine systems adapted to digital industries in the formation of a digital infrastructure for scientific, technical and industrial activities in Russia and abroad. The overall goal of digitally operating with the intellectual activity of innovative agents (scientists, engineers, managers) is to optimize [through the use of communication technologies implemented based on digital information and computing services] the processes of research, design, production and operation during the life cycle of high-tech equipment for industries industries with high requirements for the reliability of technological processes. A system organization of support for agent-oriented configuration of human-machine systems within agent-oriented associations based on the use of various forms of digital information and computing services to support intellectual activity with a significant creative component is proposed.
Exploiting the power of StarGANv2 in the wild

With wide-spread usage of style transfer, numerous methods for style transfer draw an increasing attention. Several methods to enhance the efficiency of style transformers have been made, one of them is StarGANv2, a method for multiple-style transfer, which can transform a batch of source pictures into other pictures with different styles. The main difference of StarGANv2 with other style transformers is that it uses style code to represent the styles to enable StarGANv2 to complete multiple-style transformation. The authors of StarGANv2 use CelebA-HQ and AFHQ dataset to train the model and test the model, and the results are pretty better than other style transformers. The goal of this paper is to exploit the effectiveness of StarGANv2 in the real-world scenes, such as over exposure or the angle facing the camera. The results validate the power of StarGANv2 where the model is robust enough to transfer the pictures into other styles. To achieve this, the authors of StarGANv2 use the photo clipped in videos which record real-world animals and form a new dataset. Then, the authors of StarGANv2 use the dataset to test the pre-trained model which is trained by AFHQ dataset and evaluate it according to FID metric. The authors of StarGANv2 draw a conclusion that StarGANv2 is robust in real world scenes. The meaning of this paper is that the authors get the real-world usage of StarGANv2 and have a test of StarGANv2’s robustness in real world photos and validate the potential of StarGANv2 in real-world applications.
A Potential Systematic Barrier to Community Health Literacy about Epilepsy Surgery: A Preliminary Readability Analysis of Online Health Education Materials in the United States (P6-1.006)

<h3>Objective:</h3> Analyze readability of online health education materials designed to provide epilepsy surgery information to patients. <h3>Background:</h3> Epilepsy surgery is an effective albeit underused treatment for refractory epilepsy. The workup and procedure explanations are complex and further compounded by the cognitive difficulties many people with epilepsy face. A previous United Kingdom study showed poor readability of online resources used for epilepsy surgery. However, there is still much to explore regarding the readability of resources in the United States, and what kinds of sites are associated with better readability. <h3>Design/Methods:</h3> A private browser was used to search Google for the top 100 search results for the terms “epilepsy+surgery”. Scientific papers, insurance pages, pay-wall access sites, and non-text content were excluded. The website text was re-formatted to exclude graphics, contact information, links, and headers. Readability metrics were calculated using an online readability tool (Datayze Readability Analyzer). Analysis was done through R using the Kruskal-Wallis test, and statistical assumptions were assessed. <h3>Results:</h3> Here we present the preliminary analysis of the top 100 items from a Google search yielding 76 websites and 24 exclusions. Websites were categorized as US based organizations or non-US, content from level 4 epilepsy centers, and if the sources were community health websites not associated with academic institutions. The Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL) showed significantly better readability in community health websites (FRE p=.03, FKGL p=.03), non-level 4 epilepsy centers (FRE p=.002, FKGL p=.002), and international websites (FRE p=.02, FKGL =.03). <h3>Conclusions:</h3> Health information source characteristics associated with better readability levels included non-academic centers, non-level 4 epilepsy centers and community health information websites. This analysis suggests that academic centers, especially level 4 epilepsy centers, should consider involving community members, advocacy organizations and non-medical writers in the designing of online epilepsy surgery health education materials. <b>Disclosure:</b> Mr. Seneviratne has nothing to disclose. Ms. Ho has nothing to disclose. Dr. Correa has received personal compensation in the range of $0-$499 for serving as a Consultant for Independent Medical Consultants. Dr. Correa has received personal compensation in the range of $0-$499 for serving as a Consultant for Atheneum Partners. Dr. Correa has received personal compensation in the range of $10,000-$49,999 for serving as an Editor, Associate Editor, or Editorial Advisory Board Member for American Academy of Neurology. Dr. Correa has stock in Aidin Inc. Dr. Correa has received research support from Genentech. Dr. Correa has received research support from Psi Upsilon Foundation Inc.
Diagnosis of Alzheimer’s Disease and Tauopathies on Whole Slide Images using Deep Learning Algorithm (S39.001)

Wednesday, April 26April 25, 2023Free AccessDiagnosis of Alzheimer’s Disease and Tauopathies on Whole Slide Images using Deep Learning Algorithm (S39.001)Shunsuke Koga, Minji Kim, Hiroaki Sekiya, Nicholas Martin, Monica Castanedes-Casey, Gary Yao, Dennis Dickson, and Tae Hyun HwangAuthors Info & AffiliationsApril 25, 2023 issue100 (17_supplement_2)https://doi.org/10.1212/WNL.0000000000203188 Letters to the Editor
Research on domain event extraction methods based on pre-trained model

One of the important research directions in information extraction is event extraction(EE). It aims at recognizing event types and event arguments from natural language texts, which is an important technical basis for artificial intelligence application that serves for the information work in business, science and technology, military and other fields. Currently, data annotation samples of the relevant field based on encyclopedia and news data are relatively rare and lack relevant datasets. Therefore, there are only a few public research on the event extraction in the relevant intelligence field. By integrating universal information extraction, the event extraction method which use the pre-trained model for the relevant intelligence field can handle the problem of rare data annotation samples for the event extraction in the relevant field. By expanding training samples automatically, the context information of encyclopedia and news data is learnt effectively to extract relevant events from encyclopedia and news data. Compared with other event extraction methods, using precision, recall and F1 value as assessment indicators, in event recognition tasks, the value of F1 enhances 1.26%, and in argument recognition tasks, the value of F1 enhances 1.58%. The method can significantly boost the extraction performance in small samples shown in the experimental results.
Metadatamatic: A Web application to Create a Dataset Description

This article introduces Metadatamatic, an open-source, online, user-friendly tool for generating the description of a knowledge base. It supports the description of any RDF dataset via a user-friendly web form that does not require prior knowledge of the vocabularies begin used, and can enrich the description with automatically generated statistics if the dataset is accessible from a public SPARQL endpoint. We discuss the models and methods behind the tool, and present some initial results suggesting that Metadatamatic can help in increasing the visibility of public knowledge bases.
Design Process of Lifting Crane Capacity of 300 Kilogram at PT. Pelabuhan Indonesia

Indonesia has long coastal line surrounding the country, so it becomes a maritime country. Due to this situation, the country was endowed to numerous trading via sea by utilizing numerous harbors. In harbors, there were several activities specifically about heavy equipment lifting and loading. To uplift the heavy equipment, it is necessary to develop such tools which capable to result the lifting force. Lifting crane which extensively used for heavy equipment lifting is designed to tackle that problem. The design process of lifting crane involves several efforts of planning, design process, and numerical simulation. The planning step used initial and conceptual criteria based on references. Afterwards, the design process was developed by using computer aided design of Solidworks. The numerical simulation was carried out by using ANSYS R2 2020. The design process of lifting crane has successfully done which present a comprehensive framework to model the lifting crane of capacity 300 kilograms. The resulted design of lifting crane also meets with the safety requirement for heavy equipment lifting and loading. Therefore, the result of this research would facilitate PT. Pelabuhan Indonesia to improve the lifting crane tool with high safety and robust loading capacity.