Reviewerly/exHarmony huggingface dataset:
E-Character Mental Revolution (E-CMR) based on technology of Mobile Digital Education (MDE) for physics concept

Abstract Ubiquitously, flexibility, accessibility, and a variety of cellular technology capabilities make it valuable and a necessity today. However, in general, it is underutilized in learning physics. The purpose of this study is in development of technology E-Character Mental Revolution (E-CMR) Based on Mobile Digital Education (MDE). The research method used was ADDIE (Analysis, Design, Develop, Implement, and Evaluate) with the research implementation ADDIE being 60 students and the ages 22-24 years. The results showed the development of technology of E-Character Mental Revolution (E-CMR) based on Mobile Digital Education (MDE) on the concept of physics.
Lumion animation for digital learning: Is it applicable in both Industrial and educational contexts?

Abstract Digitalization has been rapidly implemented in a variety of contexts, including industry and education. This paper sought to investigate the use of Lumion Animation for digital learning in both the industry and education. Lumion Animation was compared to such other commonly used applications as AutoCad, SketchUp, and 3DX Max. It has been found that Lumion Animation provides both practicality and completeness of users’ needs, particularly ones related to animation. It is also implied that Lumion Animation is relevant in both industrial and educational contexts.
Timing of Support in One-on-one Math Problem Solving Coaching: A Survival Analysis Approach with Multimodal Data

In this paper, we explore a kind of teaching-oriented temporal analytics on the timing of support in the context of one-on-one math problem-solving coaching. We build the analytical framework upon the human-human multimodal interaction data collected from the naturalist environments. We demonstrated the potential utility of leveraging survival analysis, a class of statistical methods to model time-to-event data, to gain insights into the timing decisions. We shed light on the heterogeneity of coaching decisions as to when to render support in connection to the problem-solving stages, coaching dyads, as well as the pre-intervention event characteristics. This work opens future avenues into a different type of human tutoring study supported by multimodal data, computational models, and statistical frameworks. This model framework may yield useful reflective teaching analytics to tutors, coaches, or teachers when further developed. We also envision that those analyses may ultimately inform the design of AI-supported autonomous agents that could learn the tutorial interaction logic from empirical data.
IMPORTANCE OF PEDAGOGICAL DISCIPLINES IN POSTGRADUATE EDUCATION OF A SUBJECT TEACHER

The purpose of this study is to substantiate the importance of pedagogical disciplines in the postgraduate education of a subject teacher. To achieve the purpose of the study, the authors had to solve the following objectives: 1) to identify the problems that novice university teachers face in the professional, psychological and motivational spheres of the adaptation process; 2) to compare the frequency of these problems in the groups of novice university teachers with pedagogical education and novice university teachers without pedagogical education obtaining postgraduate education; 3) to identify significant differences in the studied samples; 4) based on the data obtained, to draw a conclusion about the need to include pedagogical disciplines in postgraduate curricula. Methodology: 2 groups of novice teachers from Peter the Great St. Petersburg Polytechnic University (93 people) took part in this study: novice teachers of a foreign language with pedagogical education (40 people) and novice teachers without pedagogical education, obtaining postgraduate education (53 people). The study involved quantitative data analysis containing the descriptive statistical analysis and the correlation analysis. Main Findings: All novice university teachers face problems of adaptation to the professional activity. Comparison of novice university teachers with pedagogical education and postgraduate students without pedagogical education engaged in teaching resulted in the following findings: the difference between the values of novice teachers with and without a teaching degree is in most cases statistically significant. It makes it possible to conclude that novice university teachers without pedagogical education need support via additional educational programmes. This study can be useful in planning the curriculum for post-graduate students. The identified difficulties faced by young teachers without pedagogical education can be taken into consideration in the process of planning professional development programmes. Novelty/Originality of this study: This research is particularly relevant for improving the professional culture of specialists in the field of education and contributes to the solution of the professional adaptation problem faced by novice educators. The obtained results can enhance the programme of professional development of young university teachers.
Analysis of IEEE Literature Statics and Dynamics based on probability theory and correlation analysis

In recent years, the quantity of big scholarly data has a rapid growth, which brings new problems and challenges to the big scholarly data analysis. This paper employs the probability theory and correlation analysis methods to analyze the dynamics of publicly available research meta-data from IEEE official site. The experiment gives several visual evolution results of the correlations about journals and subjects, which provides some indications for future related research.
Data Reduction with Distance Correlation

Data reduction is a technique used in big data applications. Volume, velocity, and variety of data bring in time and space complexity problems to computation. While there are several approaches used for data reduction, dimension reduction and redundancy removal are among common approaches. In those approaches, data are treated as points in a large space. This paper considers the scenario of analyzing a topic for which similar multi-dimensional data are available from different sources. The problem can be stated as data reduction by source selection. This paper examines distance correlation (DC) as a technique for determining similar data sources. For demonstration, COVID-19 in the United States of America (US) is considered as the topic of analysis as it is a topic of considerable interest. Data reported by the states of US are considered as data sources. We define and use a variation of concordance for validation analysis.
Scoring the World: A Systems-Thinking Approach to Sonic Branding and Design

Research Article| April 01 2020 Scoring the World: A Systems-Thinking Approach to Sonic Branding and Design Joel Beckerman Joel Beckerman Joel Beckerman is an award-winning composer, producer, and the founder of Man Made Music—a global sonic studio in New York and Los Angeles. Man Made is dedicated to impacting everyday experiences across entertainment, technology, spaces, products, and devices for people everywhere. Beckerman has created original scores for over fifty television series and specials across major networks, including CBS, ABC, FX, NBC, and A&E. As a television soundtrack producer, Beckerman has collaborated with a wide range of artists, songwriters, and composers ranging from John Legend and John Williams to the late James Horner. He and his team have also developed signature sonic identities for global giants such as Disney, AT&T, HBO, IMAX, Hulu, and the Super Bowl on NBC. He is the coauthor of “THE SONIC BOOM: How Sound Transforms the Way We Think, Feel, and Buy,” a treatise on the topic he calls “sonic humanism.” For his work, Fast Company magazine honored him as one of their “Most Creative People in Business 1000.” Beckerman has also received ASCAP’s Most Performed Themes award for ten consecutive years. Passionate about the music community, Beckerman helped found the New York chapter of the Society of Composers and Lyricists, and proudly serves on the ASCAP board. Search for other works by this author on: This Site Google Music and the Moving Image (2020) 13 (1): 3–20. https://doi.org/10.5406/musimoviimag.13.1.0003 Cite Icon Cite Share Icon Share Facebook Twitter LinkedIn MailTo Permissions Search Site Citation Joel Beckerman; Scoring the World: A Systems-Thinking Approach to Sonic Branding and Design. Music and the Moving Image 1 January 2020; 13 (1): 3–20. doi: https://doi.org/10.5406/musimoviimag.13.1.0003 Download citation file: Zotero Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All Scholarly Publishing CollectiveUniversity of Illinois PressMusic and the Moving Image Search Advanced Search The text of this article is only available as a PDF. Copyright 2020 by the Board of Trustees of the University of Illinois2020 Article PDF first page preview Close Modal You do not currently have access to this content.
Multiple Object Detection and Tracking Using Deep Learning

The paper proposed a framework to design and develop object detection and tracking using learning based algorithms. It is an important event in security and surveillance systems using images or videos. YOLO V3 model is used for object detection and is trained using coco dataset. The objects detected are Humans, bottles, Drilling machine, Air powered saw, etc. The model detect the objects from camera field view, i.e. objects that are clearly viewed. The proposed model with pre-processing, provides an average accuracy of around 96% with different test cases.
DCVNet: Dilated Cost Volume Networks for Fast Optical Flow

The cost volume, capturing the similarity of possible correspondences across two input images, is a key ingredient in state-of-the-art optical flow approaches. When sampling correspondences to build the cost volume, a large neighborhood radius is required to deal with large displacements, introducing a significant computational burden. To address this, coarse-to-fine or recurrent processing of the cost volume is usually adopted, where correspondence sampling in a local neighborhood with a small radius suffices. In this paper, we propose an alternative by constructing cost volumes with different dilation factors to capture small and large displacements simultaneously. A U-Net with sikp connections is employed to convert the dilated cost volumes into interpolation weights between all possible captured displacements to get the optical flow. Our proposed model DCVNet only needs to process the cost volume once in a simple feedforward manner and does not rely on the sequential processing strategy. DCVNet obtains comparable accuracy to existing approaches and achieves real-time inference (30 fps on a mid-end 1080ti GPU).
An Attack on Quantum Circuits Based on the Error Rates of NISQ Systems and a Countermeasure

Noisy Intermediate Scale Quantum (NISQ) computers are subject to different sources of noise. To enhance the reliability of quantum computers, noise-aware quantum compilers are used to generate the quantum circuit. A quantum compiler maps the quantum circuit to a physical circuit that can be executed on the quantum hardware. A malicious compiler can launch several attacks to increase the error rates in the circuit, and thus, corrupt the circuit output. To detect these attacks, we utilize circuit test points, which provide the meta-information of the circuit errors, and thus, detect any unexpected changes in the circuit error rates.
The Line-Structured Light Plane Calibration based on the Plücker Line

Most of the traditional methods of light plane calibration obtain the light plane equation by extracting the feature points, but the efficiency of obtaining the feature points is low and the number is insufficient. To improve the calibration accuracy, this paper proposes a method to solve the light plane according to the Plücker matrix. This method improves the extraction accuracy of the centerline of the light bar by avoiding the intersection of the light bar with the chessboard on the target reference object and converts the center line into the Plücker matrix form. The Plücker line of world coordinated system is obtained by plane homograph. According to the external parameters, the Plücker line of camera coordinated system is obtained, the multiple Plücker lines and the plane equation are established to establish a constraint equation set, and the light plane equation parameters are obtained through SVD decomposition. Experimental results show that the optical plane composite accuracy of this method is less than 0.05mm, and its accuracy and robustness are better than the cross-ratio method.
Lingue speciali e L2: un percorso didattico attraverso Lo stivale di moda

The paper starts from the early stages of initiation to special languages and goes through its main stages, then focusing on the analysis of the multi-level study book Lo stivale di moda (Filippone, Radicchi 2014), primarily aimed at foreign learners who want to learn or deepen their knowledge of the language of fashion.  Lo stivale di moda is analyzed according to two different but intertwined perspectives: the glottodidactic perspective, in order to assess whether the study book responds, in its entirety and in its acquisition units, to the didactic programming of special languages and to the needs of adult learners; and according to the linguistic perspective, with a specific attention to the lexical level, in particular to the technical words, to the foreign words and to the words formed through the derivative and compositive processes of the Italian language.
Augmented Reality

Augmented reality is on the rise in education. This case study focuses on its incursion in the training of health professionals. The author has chosen this focus to address situations that the students do not do in the classroom because of the complexity or lack of laboratories. Thus, the author proposes to develop a mobile application with augmented reality. In the first phase, the proposal includes aspects of the technique of urethral probes, including videos and animations. The proposal also includes markers on mannequin present the information of the process for application with mannequins and patients. The results of the application are that the author identified that the augment reality enrich the process of learning for the valuation by the students and teachers. It showed that the virtual contents contribute to the education of the students of the infirmary.
Using DLT in Software Lifecycle Management

Motivated by the challenging business requirements in the area of software lifecycle management (SLM) we describe a system that is based on the use of distributed ledger technology (DLT) to address some of existing issues. DLTs and blockchain in particular allows industries to utilize distributed peer-to-peer networks where non-fully-trusting members may interact with each other without relying on the assistance of a trusted 3rd party. These interactions are kept verifiable and auditable both from the participants in the process and external players. One unexploited use of blockchain is in the area of SLM. Here providers of software products and services could benefit of some natural DLT properties. First: Establishing secure communications between non-fully trusted participants of the SLM processes and reducing the risks from malicious code reaching customer sites and their productive systems. Second: It would allow sharing of SLM resources and services between involved parties thus greatly improving the overall interaction costs required for complex multi-party procedures. Third: The system would allow better time and resource prediction for upcoming SLM procedures by keeping history execution data from previous runs of the same or similar procedures. Using DLT in SLM would allow simplification and automation of existing complex and time-consuming procedures in a cryptographically verifiable manner. Also, in some cases payments for new software or financial penalties for unplanned downtimes or other SLA infringements could be executed automatically.
Application of Rules and Authorization Key for Secured Online Training—A Survey

Online training has been present for over a decade, and its importance is increasing every day. Today, it has become very important due to ongoing COVID-19 pandemic. As it has been accepted widely by the educational systems; nowadays, challenges like hardware resources, network resources, software resource, and security have become more demanding. Security threats among all challenges require more researches to develop rigid systems where data of all stakeholders remain secured. ML has a proven track record to solve such problems. In terms of security, ML continuously learns by analyzing data to find patterns so unauthorized access to encrypted traffic is detected better and find insider threats to keep information safe. Here, a new system is being developed using an improved algorithm, described in proposed work. Using this new algorithm, machines are trained to identify unauthorized access attempts and stop them from stealing data even if, they are authenticated.
A Requirements Catalog of Mobile Geographic Information System for Data Collection

Mobile Geographic Information System (mGIS) for data collection are designed to capture, analyze and manage geographical data. The aim of this paper is to define a requirements catalog for mGIS for data collection based on the main software engineering standards, GIS standards and literature. The catalog contains functional requirements in addition to requirements about usability, internationalization (i18n), performance efficiency, reliability and sustainability. This catalog can be useful for stakeholders and developers to evaluate their apps and/or identify potential requirements for new mGIS apps for data collection.
Optimal Linear Codes Over the Field of Order 7

We construct some new linear codes over the field of order 7 to determine the exact value of the minimum length for which a linear code of dimension four with given minimum weight exists for some open cases. Most of the new codes are constructed as projective duals of some 7-divisible codes from some orbits of a projectivity in the projective space.
EFFICIENCY OF INDEPENDENT STUDENT WORK IN MODERN LIBRARY-INFORMATION SPACE

Objective : to consider the aspects affecting the effectiveness of independent work of students in the modern library and information space. Clarify the meaning of the interaction between teacher and student at all stages of independent work. Applied methods . Analysis, synthesis, comparison, generalization. Results . Some essential aspects of the use of electronic educational resources in the student's independent work are highlighted and specified. The effectiveness of the use of electronic information space at all stages of the pedagogical process is emphasized. The risks of reducing the effectiveness of independent work of students in the modern library and information space are determined. Conclusion . Self-training within the framework of self-knowledge and self-improvement requires coordination on the part of the teacher, clarification of both the value, purpose, essence of the acquired knowledge, and ethical components of the educational process. Recognizing the unconditional need for the widespread introduction of electronic information bases in the modern library and information space, the quality of the student's independent work should not be allowed to decline.
Design and Simulation of a Wide Area Search Mission: An Implementation of an Autonomous Systems Reference Architecture

The implementation and testing of autonomous and cooperative unmanned systems is challenging due to the inherent design complexity, infinite test spaces, and lack of autonomy specific measures. Simulation provides a low cost alternative to flight tests, allowing researchers to rapidly iterate on the design before fielding. To expedite this process, an Autonomous System Reference Architecture allows researchers to utilize existing software modules to rapidly develop algorithms for autonomous systems and test them in included simulation environments. In this paper, we implement ASRA on a cooperative wide area search scenario as a test bed to study ASRA's utility for rapid prototyping and evaluation of autonomous and cooperative systems. Through a face centered cubic design of experiments, selected autonomy metrics are studied to provide a response surface model to characterize the system and provide a tool to optimize mission control parameters and maximize mission performance.
Context Augmentation Aggregation Network for Nuclei Segmentation

Nuclei Segmentation plays an important role in cancer malignancy grading and assisted diagnosis. Due to the high variations of nuclei appearances among diverse cell types, this task remains challenging. Current box-free instance segmentation methods typically rely on pixel-level information. These methods tend to over- or under -segmentation due to the lack of global information. On the contrary, the box-based instance segmentation methods with object detectors perform better when locating and segmenting individual instances. In this paper, we propose a Context Augmentation Aggregation Network (CAANet) to extract discriminant features of objects of different sizes to improve the performance of segmentation. We investigate a new branch which supplements context information from multiple receptive fields. Experimental results on a publicly available Kaggle 2018 Data Science Bowl dataset shows that our method is comparable to existing methods.
A Study of Device Fingerprinting Methods

Security and privacy are the two most important issues in today’s world of Internet and communication. Most of us might think of privacy as an area of concern for those with highly sensitive data but actually, each one of us gets tracked the moment we open up our browsers. This paper tries to explore most of the major unconventional approaches of online tracking with their suitable classification into different categories. Also, it discusses how the extensions claiming of privacy enhancement themselves become a victim of the process. Further, the paper highlights the enhancement in the accuracy of the fingerprint due to the addition of the hardware and network-based techniques and the methods that can be opted to achieve an optimum level of privacy for the users in general.
Corpus and Baseline Model for Domain-Specific Entity Recognition in German

Transfer Learning approaches are a promising means to analyze low-resource domain specific texts. The German SmartData corpus is the first German corpus, annotated with entities from different domains, and thus allows to investigate transfer learning approaches for Named Entity Recognition (NER) on different domains. In order to prepare such investigations, this work includes a thorough analysis of the SmartData corpus, and a revision w.r.t. annotations and the split into training and test data, considering the distribution of document and entity types. Based on that a baseline model for NER using BiLSTM-CRF neural networks including hyperparameter optimization is presented.