Reviewerly/exHarmony huggingface dataset:
The Constructing UAV Trajectories Method Using Bezier Curves and Pythagorean Hodograph

In the proposed work, an algorithm for constructing the smooth trajectory of one UAV in a three-dimensional space is developed. To construct and approximate the trajectory, the extended Bernstein polynomials with the Pythagorean hodograph are used. The provided method uses an RRT* algorithm for path generation, and spatial Bezier curves for further trajectory smoothing. The proposed method makes UAVs apply less energy after calling the replanning procedure which is necessary for obstacle avoidance. Here we provide a quaternion representation of the Bernstein-basis Pythagorean-Hodograph curves and the proposed algorithm. We introduce simulation data that shows the pure RRT* path and the final approximated trajectory in the environment with obstacles.
A Study on the Effect of Union Membershipand Union Commitment on Welfare Attitudesof Workers in Social Welfare Institutions

The purpose of this study is to explore how participation in social welfare institutions in the labor union affects the welfare attitudes. Also, the effect of union commitment of union members among workers on the welfare attitude was analyzed.&#x0D; A self-written survey was conducted on 165 union members and 185 non-union members at social welfare institutions located in the metropolitan area. Technical statistics were analyzed, and differences in welfare attitudes between each group were investigated. A hierarchical multiple regression analysis was conducted to analyze the effect of union membership and union commitment of workers in social welfare institutions on welfare attitudes. As a result of the analysis, it was found that workers' participation in the union and union commitment had a significant effect on welfare attitudes.&#x0D; This study is significant in that it added empirical study to the welfare attitude study of social workers, which has been lacking in quantity. It is also meaningful to study the relationship between union membership and welfare attitudes, union commitment and welfare attitudes, which has not been attempted in Korea.
A Survey on the Satisfaction of Science Gifted Students for Gifted Education Program

This study aims at improving the quality of the program by evaluating the satisfaction level of students in class through surveys and interviews with students attending the G University Science Gifted Education Center. In this research, 94 students who received gifted education from March to December 2021 were surveyed by setting elements and criteria for evaluating satisfaction of gifted programs based on previous studies and revising and supplementing questions. As a result of factor analysis, five factors influencing the gifted program were derived: ‘Teaching contents’, ‘Teaching methods’, ‘Educational effects’, ‘Teacher’, and ‘Perception of the program’. As a result, multiple regression analysis was conducted to understand the relationship, the higher the educational effect and overall satisfaction. As a result of the interview, students were satisfied with the subject that science gifted programs dealt with new fields that they had never encountered in the regular curriculum, had a lot of self-directed opportunities to experiment on their own, and were familiar with class materials in real life. Based on these results, the directions to develop gifted programs in the future were suggested.
Innovations in the System of Higher Education

The article is devoted to the objects of innovative infrastructure in the education system, which are designed to create conditions for the implementation of innovative projects and programs that are essential for the development of the education system in the Russian Federation. Organizations implementing innovative projects and programs are recognized as regional or federal innovation platforms. Moscow State Pedagogical University is working to create an innovative educational system and methodological mechanisms based on the active immersion of students in scientific and technological research, and providing a new level of quality in physical education for schoolchildren and training of physicists. The introduction of the results of the study into the process of preparing a university graduate to work in a modern school will allow him to form new types of professional activities that are in demand by society at the present time, and successfully solve the tasks set for the education system,including teaching physics. The model can be broadcast and replicated in any region of the Russian Federation. Ensuring the effective operation of new educational programs, educational technologies, mechanisms, forms and methods of education management is due to the opportunities provided by associations of universities with innovative companies.
The Love to Read Programme

The Love to Read Programme&#x0D; Oxley, E; Ricketts, J; Shapiro, L &amp; McGeown, S.&#x0D; &#x0D; Collaborative research practices, which involve children, young people, teachers and/or stakeholders partnering in research, draws upon the distinct, yet complementary knowledge, expertise and experience of each. Collaborative research approaches have potential to narrow the gap between educational research and practice (NFER, 2017) and position the needs and experiences of stakeholders at the centre of the research (Calderón López &amp; Theriault, 2017).&#x0D; &#x0D; This poster describes the Love to Read project, which aims to increase children’s reading motivation and engagement by synthesising relevant theory and research, with children’s ideas and experiences, and teachers' pedagogical expertise. In Phase 1, (Phase 1 preregistration: https://osf.io/5ztjk), 59 demographically diverse children from across the UK, with different reading attitudes and experiences, participated in online or in-person interviews. An inductive data-driven approach to thematic analysis was used (Braun &amp; Clarke, 2006) to understand the diversity of children’s book reading experiences and children’s ideas for practices to promote reading motivation and engagement. In Phase 2, children’s insights were shared with teachers, as the research team and teachers collaborated to co-design a professional development programme aimed at increasing reading motivation and engagement in children (Phase 2 preregistration:https://osf.io/xsjhc). The final part of Phase 2 aims to evaluate the co-design process, from participating teachers’ and researchers’ perspectives.&#x0D; While pre-registration has recently gained momentum in qualitative research, especially experimental studies, open science practices are used considerably less in qualitative research. The Love to Read project has pre-registered all qualitative methods for Phases 1 and 2, including interview schedules and data analysis protocols. Traditionally, preregistration is a tool used to distinguish exploratory and confirmatory research. Qualitative research, however, is exploratory by nature. For example, using data-driven thematic analysis meant hypotheses could not be drawn in advance, as this could have created bias in our analysis. Furthermore, interview schedules can change or adapt depending on the responses from the interviewee. Therefore, strict compliance to methods such as those which would take place for quantitative data collection are not wholly possible. Nonetheless, using pre-registration should still be encouraged for qualitative researchers to add credibility and transparency of their research.&#x0D; This project uses co-design, with children, teachers and other professionals, creating a unique opportunity to develop a professional learning programme which is likely to be engaging and relevant to children, and acceptable and feasible to teachers, maximising the likelihood of uptake, and successful and sustained implementation. The project completion will result in free and openly available continued professional development materials for teachers.
Axiological dimensions in COVID-19 pandemic discourses

The global pandemic caused by the novel coronavirus has led to a series of actions at the political, economic, and social levels unprecedented so far. Due to the high risk of contagion, by both air and human touch, governments in many countries around the world have resorted to sets of measures, some even drastic, aimed at restricting and reducing, as far as possible, the physical closeness between people. These measures affected to different extents life in society as we knew it, not only economic and cultural life but also social interactions and activities, communication, and inter-relationships between people. In general, the measures were justified at the political level through the attempts to keep the number of illnesses and deaths to a minimum. This chapter analyses comparatively how the actions, some of them severe, to restrict social life were justified in speeches announcing these measures by the heads of state in three European countries: Germany, France, and Romania, in March 2020, when the COVID-19 pandemic spread through Europe. Through a thematic discourse analysis, it examines the extent to which axiological and ethical issues have been invoked in these discourses, what axiological and ethical dimensions have been emphasized, and how they have been used to justify measures that have entailed social restrictions, including those on certain rights and freedoms. Moreover, it analyses the similarities and differences in terms of ethical and value-centred dimensions and cultural norms present, as well as in terms of their justificatory utilization, between the discourses of the heads of state of the three countries regarded by the study.
Challenges and Potentialities of Using ICT in Initial Teacher Education: A Comparative Study With Students From Portugal and Spain

The use of digital technologies in a conscious, critical and creative way is one of the challenges proposed in initial teacher training, since we are witnessing a time of change that requires the preparation of future teachers for the 21st century. This article is part of the IFITIC Project which aims to rethink educational practice
To-Do List Using Map APIs

To-Do List by the name indicated smartly makes it way in analyzing user’s likes and dislikes and the time period the user is willing to explore a place and gives him with Amazing results in the form where utilization of time is maximum. This system is basically used to help a traveller new to a city or anyone who wants to explore a city in the given time period, the system makes use of the preferences of the user to get all the locations and places with all their information to sort and give a plan to the user. This project has four modules from signing in to the final map view display. This application will be helpful for the user to schedule a trip to a couple of places in the minimum distance within the time period provided as per user’s requirement. The final output is a map view with the connected path of smaller route to reach the multiple places as per user’s interest. Thus we have used Wamp Server for combining PHP, MySQL, FourSquare API and Tom Tom Maps API to create this application.
27 Combining Machine Learning and Network Science to Cluster Emergency Department Chief Complaints and Diagnoses

Study Objectives: Improvements to electronic health record (EHR) systems have enabled the adaptation of emergency care practice to incorporate discrete data capture of chief complaints and clinical diagnoses. However, the number of distinct data elements for complaints and diagnoses is very large. In this study, we sought to apply data science approaches (including network science and unsupervised machine learning) to identify clusters of complaints and diagnoses in the emergency department (ED).
Text Summarization Using Deep Learning

In the big data era, there has been an explosion in the amount of text data from a variety of sources. This volume of text is an inestimable source of information and knowledge which needs to be effectively summarized to be useful. There are plenty of text material available on the internet. Earlier traditional approaches for extractive text summarization have been heavily dependent on human engineered features. However, it is a laborious and tedious task. In this paper, a data-driven approach has been used to generate extractive summaries using deep learning. So there is a problem of searching for relevant documents from the number of documents available, and absorbing relevant information from it. Thus, the need for a solution emerges, that transforms this vast raw information into useful data which a human brain can understand. One such common technique in research that helps in dealing with enormous data is text summarization. We must first comprehend what a summary is before moving on to text summarization. A summary is a text created from one or more texts that delivers key information from the source material in a condensed style. The most significant benefit of adopting a summary is that it cuts down on reading time. Text summarization is the process of extracting the most important meaningful information from a document or set of related documents and compressing it into a shorter version while retaining its overall meanings. Automatic summary is a well-known method for refining a document's important points. It works by providing a reduced version of the text that preserves significant information. There are two types of text summarization methods: Extractive and Abstractive.
Analysis of Women Safety in Indian Cities Using Machine Learning on Tweets

Women and girls have been experiencing a lot of violence and harassment in public places in various cities starting from stalking and leading to abuse harassment or abuse assault. This research paper basically focuses on the role of social media in promoting the safety of women in Indian cities with special reference to the role of social media websites and applications including Twitter platform Facebook and Instagram. This paper also focuses on how a sense of responsibility on part of Indian society can be developed by the common Indian people so that we should focus on the safety of women surrounding them. Tweets on Twitter which usually contain images and text and also written messages and quotes which focus on the safety of women in Indian cities can be used to read a message amongst the Indian Youth Culture and educate people to take strict action and punish those who harass the women. Twitter and other Twitter handles which include hashtag messages that are widely spread across the whole globe sir as a platform for women to express their views about how they feel while we go out for work or travel in a public transport and what is the state of their mind when they are surrounded by unknown men and whether these women feel safe or not?
Inertia alignment of phase-shifting algorithms for high-numerical-aperture spherical testing in Fizeau interferometry

In Fizeau interferometry for high-numerical-aperture spherical surface tests, the mechanical phase shift becomes spatially nonuniform within the observation aperture. We divided the aperture into annular regions and calculated the object phase using several algorithms designed for different phase shifts. The division substantially decreased the nonuniformity; however, it caused bias errors at the regional boundaries in the measured phase. The error is due to the different error coefficients of the algorithms for the phase-shift nonlinearity. A convolution technique that modifies a sampling window to align the error coefficients of a set of algorithms is proposed. The technique is experimentally shown to minimize phase measurement errors.
Inspiring Innovation through Design Thinking: Lessons from a Graduate-Level Course Offered during the Pandemic in Pakistan

There is a consensus that in a world impacted by COVID-19, the relationship between education and technology must be re-considered. Design Thinking has been an effective technique for fostering innovative thinking. Theis paper discusses the application of Design Thinking as a pedagogical innovation at the Aga Khan University Institute for Educational Development Pakistan in a graduate-level online course for teachers. Participants were invited to learn about the Design Thinking process and technology integration by engaging in a Design Thinking process to identify a problem and develop ideas needed in their professional teaching contexts. Data were analysed using an autoethnographic approach to determine the effectiveness of Design Thinking in inspiring innovations in education. Design Thinking was a novel approach for the participants, and many stated they will include it in their work in the future. The participants' design problems were related to evaluation, learner engagement, and online and technology-enhanced learning ethics. The empathy stage helped in a deeper understanding of taken-for-granted teaching issues. The process encouraged participation and voice, particularly among the female participants. Teacher education must adapt to encourage innovations in classrooms. Educators in similar contexts may find the lessons valuable.
FACIAL LANDMARK DETECTION WITH MEDIAPIPE &amp; CREATING ANIMATED SNAPCHAT FILTERS

MediaPipe Face Mesh is a face geometry solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D surface geometry, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance critical for live experiences. There are two models and they are face detection and face landmark model.Face landmark screen coordinates are converted into the Metric 3D space coordinates; face pose transformation matrix is estimated as a rigid linear mapping from the canonical face metric landmark set into the runtime face metric landmark set in a way that minimizes a difference between the two; a face mesh is created using the runtime face metric landmarks as the vertex positions (XYZ), while both the vertex texture coordinates (UV) and the triangular topology are inherited from the canonical face model.Snapchat Filter Controlled by Facial Expressions: Currently, our face expression recognizer can check whether the eyes and mouth are open or not so to get the most out of it, we can overlay scalable eyes images on top of the eyes of the user when his eyes are open and a video of fire coming out of the mouth of the user when the mouth is open.
Based on Blended Action Learning to Improve Creative Problem-Solving Ability Development and Application of Cultural Contents Class Model: Focused on Video Content Class

Cultural contents require a complex and holistic approach while responding to technological developments entering the 4th industrial age. For this, creativity based on the humanities is required. It is very important to improve creative problem-solving ability based on creativity, and methodological research to improve it while applying it to real problems is urgently needed. In this study, we propose an action learning-based video content class model to cultivate creativity and creative problem-solving ability. In addition, reflecting the reality that classes beyond face-to-face classes are needed due to COVID-19, the expansion of online and offline blended action learning was promoted. Through this study, it is hoped that the study of the cultural content class model that is helpful in solving practical problems will be continuously realized, and I hope that the diversity of cultural content at the interface between the humanities and technology will be made more actively.
Applying Evidence-Centered Design to Assess Learner Competency Levels in VR Learning Experiences

When designing virtual reality (VR) training, it's important that VR learning experiences output the proper data to measure learning and drive evidence-based insights about learner competency levels. This presentation proposes using the Evidence-Centered Design for Assessment (ECD) framework for designing VR experiences to ensure learning activities are aligned to competency indicators thatproduce learner data that can be evaluated to assess mastery levels. The ECD framework can bring value to VR learning solutions by providing a method of embedding assessments directly within the learning experience without breaking immersion or disrupting flow. In the ECD framework, evidence of learning is directly tied to and measured by a learner’s actions within the VR environment, providing empirical data that practitioners and organizations can use to make inferences about a learner’s competency levels. This presentation will detail how to implement ECD into VR learning experiences and ensure that the solution’s instructional design is strategic and measurable, by leveraging three main models: Competency Model, Evidence Model, and Task Model.
New Efficacies for Audience/Performer Interactivity and Responsive Narrative in Immersive Theatre

Immersive virtual reality (IVR) has substantial possibilities for students to learn remotely through exploration, collaboration, and socialization. IVR is well suited to theatre, which relies on interpersonal attributes to demonstrate actor relationships and character development. IVR theatre can break down the fourth wall to connect audience members and actors in the same physical space, thereby removing the barrier of the stage and placing the audience within the storyline. In this study, a high-caliber youth theatre group was tasked with writing, workshopping, directing, rehearsing, and performing a play for a live audience in AltspaceVR. Grounded by current literature on the affordances and limitations of IVR for learning, this research followed six high school students imagining, designing, and delivering an immersive theatrical performance. Findings report how youth are experimenting with immersive technologies to take traditional theatre in new directions, including audience interaction, responsive narrative, and actors/actresses performing as digital avatars. We highlight pedagogical strategies and design recommendations for working with youth to integrate IVR theatre experiences in secondary education.
Sequential recommendation method integrating item relationship and user preference

The sequential recommendation aims to recommend items that may be of interest to users based on user behavior sequence information. However, most of the current sequential recommendation tasks cannot adequately model the longterm preferences and short-term intentions of users when mining user preferences. In order to model and integrate the user's long-term and short-term preferences effectively, a new sequential recommendation method, which integrates item relationship and user preference, named IRUP, is proposed. Firstly, Graph Convolution Network (GCN) and an itemrelation level attention mechanism are utilized to model long-term and short-term preferences of users respectively; secondly, a co-attention mechanism is used to learn the cross-correlation information between long-term and short-term preferences, which enhances the user's preference representation; finally, the long-term preference and the short-term preference are fused, and the inner product is introduced to calculate the recommendation list. The experimental results on two public datasets Beauty and Home show that the proposed method IRUP can effectively improve the recommendation performance. Compared with the best baseline method KDA, the two evaluation metrics HR@5 and NDCG@5 have an average improvement of 8.28% and 7.03%, respectively.