Reviewerly/exHarmony huggingface dataset:
Meta-Interface Analysis for Interaction in Mobile Augmented Reality

Mobile Augmented Reality has expanded including the cultural heritage sector. Among the options offered is the digitization of cultural heritage. Multiple technical breakthroughs has implemented, including hand gesture recognition and body tracking, into mobile augmented reality systems. The success of these improvements depends on a good user interface. Meta User Interface (Meta-UI) allows significant information to be displayed without interfering with system operation. The results of the analyses that the Meta-UI user interface could aid users in employing hand gestures and body motion capture on this mobile augmented reality without any issues and could deliver information about batik efficiently. PIECES Framework testing confirmed this, with a satisfaction score of 4.40 to 4.55. Using the PIECES Framework concepts and questionnaire that focus on user satisfaction with mobile augmented reality, the score indicates that the user is satisfied.
Rancang dan Bangun Aplikasi Chatbot Menggunakan Pendekatan Natural Language Processing (NLP) Pada Pusat Pelatihan Inatechno

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Prediksi Penjualan Online bagi Pelaku Industri Rumahan selama Pandemi Covid-19 Menggunakan Jaringan Syaraf Tiruan

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ANALIZA NAČINA PISANjA SAŽETAKA U ČASOPISU „LIPAR“

This paper deals with the manner of writing abstracts for the scientific papers published in the journal Lipar. The aim of the paper is to determine which information the authors of abstracts list when writing them and how much their man- ner of writing deviates from the theoretic rules of writing this element of scientific- critical apparatus. For this purpose, we collected a corpus of 50 scientific abstracts whose structure was compared with the model abstract formed by combining models offered in the journal Lipar and in the works we cited. The results of the research were as follows: 1) no example of the so-called all-inclusive model of a scientific abstract; 2) a total of 13 models was found; 3) the models subject (corpus) + method + goal + result and subject (corpus) + method + goal proved to be the most common ones in the corpus, but not significantly more common than the remaining models. Based on the listed results, we may conclude that the manner of writing a scientific abstract is far more diversified than the referenced works show.
Google Site-Based Service and Trade Accounting Practice Learning Media for Grade XI Accounting Students

The learning process is still using conventional learning methods. The teacher uses the module to explain the teaching material that the students have not understood by using the blackboard media. This study aims to develop Google Site-based Service and Trade Accounting Practice Learning Media for class XI accounting students. This research is development research adapted from the ADDIE development model. The Data was collected through questionnaires. The data obtained from the questionnaire were analyzed descriptively, qualitatively, and quantitatively. The study’s results consisted of five stages of making a Google Site-based Service &amp; scoping Service &amp;s accounting practice learning media. The eligibility level of Google Site-based Service &amp; Trade Accounting Practice Learning Media based on assessments: Material Experts obtained a percentage of 92.61% which belongs to the Very Decent category, and Media Experts obtained a percentage of 88.89% belongs to the Very Decent category. The feasibility assessment by the trial students obtained a percentage of 88.61% which belonged to the Very Worthy category. Thus, the Google Site-based Service &amp; Trade Accounting Practice Learning Media is very suitable for learning. Meanwhile, the results of the pre-test and post-test scores stated an increase in the average after the google site-based accounting learning media was tested from 65 to 80.
Factors associated with contact tracing compliance among communities of color in the first year of the COVID-19 pandemic

The disproportionate impact of COVID-19 on communities of color has raised questions about the unique experiences within these communities not only in terms of becoming infected with COVID-19 but also mitigating its spread. The utility of contact tracing for managing community spread and supporting economic reopening is contingent upon, in part, compliance with contact tracer requests. We investigated how trust in and knowledge of contact tracers influence intentions to comply with tracing requests and whether or not these relationships and associated antecedent factors differ between communities of color. Data were collected from a U.S. sample of 533 survey respondents from Fall (2020) to Spring 2021. Multi-group SEM tested quantitative study hypotheses separately for Black, AAPI, Latinx, and White sub-samples. Qualitative data were collected via open-ended questions to inform the roles of trust and knowledge in contact tracing compliance. Trust in contact tracers was associated with increased intentions to comply with tracing requests and significantly mediated the positive relationship between trust in healthcare professionals and government health officials with compliance intentions. Yet, the indirect effects of trust in government health officials on compliance intentions were significantly weaker for the Black, Latinx, and AAPI samples compared to Whites, suggesting this strategy for increasing compliance may not be as effective among communities of color. Health literacy and contact tracing knowledge played a more limited role in predicting compliance intentions directly or indirectly, and one that was inconsistent across racial groups. Qualitative results reinforce the importance of trust relative to knowledge for increasing tracing compliance intentions. Building trust in contact tracers, more so than increasing knowledge, may be key to encouraging contact tracing compliance. Differences among communities of color and between these communities and Whites inform the policy recommendations provided for improving contact tracing success.
Blockchain and Bitcoin: What It Means for Power Electronics [Industry Pulse]

A perpetually hot topic in the news these days seems to be cryptocurrencies, and more broadly, blockchain technologies. After following some of the ups and downs from the past few months (and years), I wanted to take a look at where the technology has been and where it’s headed—and how it will impact the power electronics industry. I’m not going to get too far into the details on how blockchain works here—for a deep dive into the technology, check out the November/December 2022 issue of IEEE Potentials: Blockchain Technology; Societal Impacts, Education and Research.
Technologies and the Serial Attitude

Serialism is often canonically pinned to a few mid-century acoustic pieces, but this textbook definition is unnecessarily narrow. Would it be possible to consider computer music, EDM, and hip hop as serial, in some way? This essay argues that a ‘serial attitude’ emerges in the dialectic between analogue and digital ways of musicking. Electronic technologies – from generators to drum machines – crucially mediate such attitudes and behaviours. In sum, serial attitudes shape and are shaped by technological affordances. Case studies include the analogue electronic studio of the WDR, early computer music laboratories at Utrecht, Bell Labs, and Columbia-Princeton, and the vernacular musics of Yellow Magic Orchestra and Afrika Bambaataa. I explore resonances between these disparate scenes, while also arguing for their particularity. This essay rethinks serialism as a practice imbricated with technology, extending beyond the narrow confines of high-art academic institutions.
Unsupervised white blood cell characterization in the latent space of a variational autoencoder

Leukemia diagnosis and therapy planning are both based on classifying peripheral blood images, under a high inter/intra observer variability scenario. In such applications, automatic image processing and classification strategies have obtained outstanding recognition results, however they are fully dependent on the quality of the annotated data. Unlike supervised classification approaches which built upon label-transformations, the herein presented methodology introduces an unsupervised White Blood Cell characterization in the latent space of a Variational Autoencoder (VAE). The latent space is constructed upon 128 parameters from 64 gaussian distributions and then a k-means clustering may retrieve leukemia diagnostic meaningful cell groups. The whole procedure is twofold assessed: 1) evaluation of the 128 dimension VAE latent space for differentiating cells with higher diagnostic value (blast cells) from other peripheral blood components under multiple supervised classification strategies, and 2) quantification of VAE-parameter clustering capacity to unsupervised separation of blast and non-blast cells. Obtained accuracies of each experiment, 0.888 and 0.757 respectively, suggest that the presented strategy successfully characterizes white blood cells and provides a representation space where subtle cell differences can be objectively measured.
Anthropogenic material flow – a geologic factor

With the industrial production anthropogenic material flows have been growing exponentially. These man-moved material flows include earth material like rock, soil, water, waste, natural gas and others. With 35 km3 per year the amount of movement induced by man exceeds the geogenic mass flow in the exogenic cycle. The impact of the technologically induced movements can be seen all over the globe. Subsidence causes rivers to reverse the direction of flow or flooding of coastal and mining areas. Stockpiling of waste and overburden increases the rate of erosion on slopes. Displacement of geogenically bound sulfides results in acidification of bodies of water and soil in addition to acid rain. Since man-induced material flows in volume are comparable to geogenic mass movements/transport geology as a science has to be called up to provide predictive understanding of the dynamics of such human-induced changes.
Preserving human privacy in real estate listing applications by deep learning methods

The images are important components of real estate applications on the internet to inform users. There are multiple rental and sale properties and many images of these properties on the internet, and it is challenging to control the images of these real estate in terms of time, workload, and cost. Considering the requirements of the problem, Deep Learning (DL), one of the Artificial Intelligence (AI) methods, offers ideal solutions. This study aims to distinguish images that contain humans using deep learning techniques. This will also aid in not violating the privacy of people according to the Law on the Protection of Personal Data in the image content used in real estate applications. For this purpose, firstly, a dataset of real estate images with and without humans called the Real Estate Privacy (REP) dataset was created. The REP dataset was split into 70%, 20%, and 10% for training, validation, and testing, respectively. Secondly, the REP dataset was trained with Inceptionv3, ResNet-50, and DenseNet-169 architectures using transfer learning. Lastly, the performances of the architectures were evaluated by accuracy, precision, recall, and F1-score accuracy metrics. Experimental results indicate that the 52 epoch ResNet-50 architecture is the best for our datasets with 98.45% overall accuracy and 98.00% precision, 98.90% recall, and 98.44% F1-score. The Inceptionv3 model provided the best results on the 55th epoch with 98.27% accuracy, 97.81% precision, 98.71% recall, and 98.26% F1-score. Finally, the DenseNet-169 model produced the best results on the 47th epoch, with 97.81% accuracy, 97.09% precision, 98.52% recall, and 97.80% F1-score. Accuracy assessment shows that the highest accuracy among the three architectures was obtained with the ResNet-50 architecture This study shows that deep learning methods offer a perspective to image content control and can be used efficiently in real estate applications.
Secondary School in Russia: the Collective Portrait and Prospects. Part 2

The article presents the detailed analysis of a secondary school in the Russian Federation. The following blocks have been studied: ‘Strategy for education’, ‘Learners’, ‘Process of education’, ‘Teachers’, ‘Education environment’, ‘Management’, ‘Financial means and Information support’, each of which includes from 5 to 20 indicators. Each indicator was examined separately on the basis of the latest statistical data, political, social, psychological and pedagogical researches and received an assumed index from 1 to 9. It laid the foundation for the design of the secondary education establishment (SEE) model, the major purpose of which is the introduction of the cohesive and detailed portrait of the SEE in order to enhance its development, equity and quality of education. In conclusion, each block of indicators has got the outcome that together permit not only boosting the quality of education, but also upgrading the school design along with raising its social status. Moreover, some scientific deficiencies have been detected that may serve a road map for new research in pedagogy and linked disciplines.
Research Readiness of Military University Teachers Is a Factor in Improving the Level of Training of Highly Qualified Specialists

The use of new forms and methods of interaction between a teacher and a future officer in the modern educational process is due to their availability, quality and effectiveness. One of the main directions of the cadet’s educational activity is scientific work, which is based on the results of research conducted under the guidance of a teacher. The presented analysis of the guiding documents defining the criteria for the appointment of the teaching staff made it possible to establish the requirements for candidates and the specifics of their selection, in connection with which a problem was identified in the organization of scientific work for a novice teacher. Empirical data obtained during the monitoring of the scientific work of the faculty of the Perm Military Institute of Rosgvardiya for 2021 allowed us to determine its key indicators, which reflect all types of scientific work and have a point equivalent, depending on the level, type and personal contribution of the participant of scientific work.
Comprehensive Organization of Extracurricular Activities and a Program of Educational Work

The article discusses the relationship between extracurricular activities and educational work in accordance with the updated Federal State Educational Standard for Primary General Education.
Implementation of the Requirements of the Updated Standard When Introducing New Concepts in Mathematics Lessons

The article is based on the main key ideas of the formation of the planned subject and meta-subject results. The article discusses the methodology for implementing the requirements of the updated standard, taking into account the goals of teaching mathematics. An approach is proposed to the formation of individual skills of cognitive universal educational actions of 5th grade students in teaching mathematics, using learning tasks and learning tasks that develop the ability to solve a wide range of problems.
Technology Is Top of Mind at Second Water 2050 Think Tank

Journal AWWAVolume 115, Issue 2 p. 7-9 Water 2050 Technology Is Top of Mind at Second Water 2050 Think Tank Greg Kail, Corresponding Author Greg Kail [email protected] Search for more papers by this author Greg Kail, Corresponding Author Greg Kail [email protected] Search for more papers by this author First published: 06 March 2023 https://doi.org/10.1002/awwa.2049Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume115, Issue2March 2023Pages 7-9 RelatedInformation
Translation Technology in Canada

This chapter traces the evolution of translation technology in Canada, from the emergence of the first computerized aids (dedicated word processors), through the well-known success of the Météo system, to the development of innovative translator support tools like TransType. We also assess the current use of cutting-edge technologies like statistical MT and automatic dictation for the production of high-quality translation.
QUICK RESPONSE CODE PADA SISTEM INFORMASI KEHADIRAN GURU DAN SISWA SMK NURUL MUHTADIN

Attendance is an activity that must be carried out in various activities, one of which is in teaching and learning activities in schools, lectures, seminars, meetings, teacher attendance, and others. In teaching and learning activities in schools and terms of teacher absenteeism, attendance is an important parameter because it can affect student success and teacher performance in the continuity of teaching and learning activities, especially at SMK Nurul Muhtadin Kibin. At this time, the attendance system at SMK Nurul Muhtadin Kibin school attendance activities for teachers and students is still using the conventional way, namely the teacher in the class mentions the names of students one by one and then puts a dot on the attendance book for each class that has been prepared by the school and for attendance teachers have administrative officers who go around checking each class by using paper as a medium for recording teacher absences. This method is certainly very risk when the attendance book is lost or damaged so that the loss of attendance information that has been carried out, as well as for making teacher attendance reports takes a little longer and risks errors in reporting teacher absenteeism. The use of QR CODE in the development of a web-based Teacher and Student Attendance Information System is expected to solve existing problems. The system that built by this author uses the PHP version 7 programming language, MySQL as the database media. The development method that will be used by the author is to use the Waterfall method. With the presence of a teacher and student attendance information system using this QR Code, the author to overcome the problems faced by making it easier for students and teachers who want to take attendance.
Open-Source Machine Translation Technology

After defining free/open-source (FOS) software and licensing, implications for machine translation (MT) as data-intensive software are reviewed. The types of FOS MT systems and users and their use in business and research are reviewed. Existing FOS MT systems are surveyed and the challenges ahead for FOS MT are described.
Pragmatics-Based Machine Translation

Pragmatics-based machine translation relies on reasoning to determine speech act content and on belief ascription for modeling the participants in the translation process (source text author and audience, translator, intended audience of translation). The theoretical framework and computational platform are presented along with an analysis of their benefits and shortcomings.
Computer-Aided Translation

This chapter discusses the seven major concepts in computer-aided translation that shape the development of functions in translation technology. These concepts are: simulativity, emulativity, customizability, compatibility, controllability, productivity, and collaborativity.
Part-of-Speech Tagging

Part-of-speech tagging is a well-known problem and a common step in natural language processing applications; part-of-speech taggers try to assign the correct part of speech to all words of a given text. This chapter reviews the main approaches to part-of-speech tagging and their use in machine translation.
An Efficient Task Synthesis Method Based on Subspace Differential Patterns for Arrangements of Event Intervals Mining in the Avionics Cloud System Architecture

Avionics Cloud is a new multi-platform avionics system architecture that provides dynamic access, resource pooling, intelligent scheduling, on-demand service and other cloud computing features. Using Avionics Cloud to rationalize the order of multi-flight platform task execution and realize multitask synthesis is a challenging problem. In this paper, we propose an Efficient Task Synthesis Method based on Subspace Differential Patterns for Arrangements of Event Intervals Mining-DiMining. For tasks executed in a multi-platform Avionics Cloud system with dynamic characteristics of time intervals, DiMining is proposed. The algorithm mines the differential frequent task execution event interval patterns related to execution efficiency from the scenario dataset with high execution efficiency and the scenario dataset with low execution efficiency in order to identify key task patterns related to execution efficiency and improve the task synthesis design efficiency of the multi-platform Avionics Cloud system. Furthermore, in order to improve the mining efficiency of the algorithm, this algorithm designs a variety of pruning strategies to ensure that two differential time interval patterns with high and low functional execution efficiency are mined at one time without preserving the set of candidate items. The experimental results show that the DiMining algorithm is more efficient than the traditional algorithm on the open dataset. The DiMining algorithm is used to mine the 350-field high-efficiency operation scenario dataset and the 350-field efficiency operation scenario dataset under the constructed typical UAV cluster co-detection task scenarios. Based on the simulation results, the DiMining algorithm is able to effectively support the design of multi-platform Avionics Cloud system task synthesis architecture and improve the efficiency of UAV cluster collaborative detection.
Design of a Hybrid Movie Recommender System Using Machine Learning

The primary aim of recommender system is to predict items which are of most interest to the users and today recommender systems play a vital role in boosting the sales in any e-commerce based platform. The present paper proposes an approach for recommending movies to the users on the basis on their choices. A novel technique for evaluation of collaborative filtering using SVD and hit ratio as a metric is taken in our proposed approach. We attempted to build a model-based Collaborative filtering technique. The proposed paper makes use of matrix factorization techniques like SVD &amp; SVD++ for filtering movie recommendation system based on latent features. It makes better recommendations based on choice of user because it captures the underlying features driving the raw data. In this paper we are proposing a hybrid recommender system fusion of Content Based and SVD to get a new hybrid recommender system. Our proposed model gives the value of RMSE 0.87 for SVD model and RMSE 0.938 for SVD++ model. Keywords-- Collaborative filtering, movie recommendation, SVD, content based filtering
THE ROLE OF RAYTRACING IN THE UNIVERSE OF GAME DEVELOPMENT

THE ROLE OF RAYTRACING IN THE UNIVERSE OF GAME DEVELOPMENT Yernar Aldabergenov student, International Information Technology University, Kazakhstan, Almaty Nurzhan Duzbaeyv PhD, associate Professor, International Information Technology