Reviewerly/exHarmony huggingface dataset:
Supporting Remote Students Through Utilizing Web-Based Exercise-Templates and a Mobile Learning Chatbot for Creating and Interacting with Learning Materials

During COVID-19 pandemic, and in the post-pandemic era, the dependency on digital learning tools and integrating them into regular teaching practices revealed several challenges and requirements from those tools. Such tools are needed to accommodate existing learning materials that teachers use, and deliver them to students who are learning remotely. In this paper, we demonstrate a mobile learning approach for supporting remote students and teachers. Our proposed approach utilizes a pedagogically informed design of exercise templates to construct learning materials as stand-alone exercises. A web application is designed to enable teachers of creating those exercises. On the learner’s side, a Chatbot-based mobile application is developed to ensure an easy and understandable interaction with the system for young students. Students could engage in a conversation with the Chatbot, solve exercises and get predefined teacher feedback on their solutions, all without a direct contact with the teacher who created those exercises. We implement our system and test it in three European contexts, in Spain, Greece and Germany. Our evaluation reveals high acceptance of the system’s ability to integrate existing materials to offer them to remote students; high student engagement with the learning Chatbot; and several lessons-learned from the user interaction with the system.
Augmented Reality Technology Applied to Surgical Planning in Oncological Colorectal Surgery

This paper describes the application of augmented reality technology from three-dimensional colon models as a method of preoperative planning in oncological colorectal surgery. We have developed holograms of augmented reality from threedimensional anatomical models of the colon, obtained from computed tomography images (Siemens Somatom Perspective 64) with abdominal image cuts 3 mm thick. The recovery of the images was in DICOM format. The processing to achieve the threedimensional reconstruction was performed with the program OsiriX, which made a complete segmentation of the colon surface and modified the image density. 3D models were obtained of the isolated colon and in relationship with the bony structures. The smartphone Colon 3D AR application was designed (increased hyper experience- visualizer with SLAM technology) to apply augmented reality technology. An individualized hologram of augmented reality (scale 1:1) was created from each three-dimensional model. A projection with the smartphone on the patient's abdomen was made by modifying the position in the height of the reconstruction, using the pelvic bones as an anatomic reference point to calibrate the hologram's orientation. Three-dimensional reconstruction of the tumor in the preoperative plan of oncological colorectal surgery, combined with hyperreality technology, allows developing augmented reality models to improve colon anatomy knowledge and plan the surgical technique. The application is easy to use and may have advantages in preoperative colon surgery planning.
Structured Specification of Paraconsistent Transition Systems

This paper sets the basis for a compositional and structured approach to the specification of paraconsistent transitions systems, framed as an institution. The latter and theirs logics were previously introduced in [CMB22] to deal with scenarios of inconsistency in which several requirements are on stake, either reinforcing or contradicting each other.
Game Lino dalam Pembelajaran Bahasa Inggris Materi Many Things Kelas VII Sekolah Menengah Pertama

English is an international language where many countries use English in their daily life, such as in Malaysia. English with "Many Things" material, which is a material in English learning that teaches students to get to know the objects around them, not only knowing them but here students also learn how to write them. The problem in real life is that books do not play a role in children learning English because the books only display text and pictures so that many students do not know how to pronounce the English they are learning. With this Lino game, students can get to know the objects around them by writing the names of the objects displayed in the game and listening to how to kiss what they have written. This game serves to make it easier for children to learn English quickly, and not only that, with this game, students in learning also feel entertained by the attractive animation display.
Intelligent Task Scheduling Using Bat and Harmony Optimization

Cloud computing describes computer services provided through the internet and includes a wide range of virtualization resources. Because cloud computing is made up of a sizable number of heterogeneous autonomous systems with an adaptable computational architecture, it has been widely adopted by many businesses. The scheduling and management of resource utilization, however, have become more difficult as a result of cloud computing. Task scheduling is crucial, and this procedure must schedule tasks on the virtual machine while using the least amount of time possible. Utilizing an effective scheduling strategy enhances and expedites cloud computing services. Optimization techniques are used to resolve cloud scheduling problems. The purpose of this research is to address tasks distribution within the system to improve system performance overall and reduce task execution time. Two well-known optimization algorithms (the Bat, and Harmony search algorithms) were used in this approach as well as a combination approach Bat Algorithm Harmony Search ( BAHS ) that integrates the two. When compared to the other algorithms used for task scheduling, the (BAHS) method was chosen because it is flexible and produces effective results. Tests were run on a dataset that was created randomly. The suggested algorithm results were compared to the other popular algorithms in the field. The results show that the suggested swarm-based scheduling techniques can produce more accurate results than those of the competing algorithms in terms of the makespan , mean, and standard division.
Utopías y distopías en el contexto del COVID-19: una experiencia con estudiantes normalistas

The objective of this research was to explore the educational transformations experienced by sixteen students in teacher training during the COVID-19 pandemic. The qualitative approach was used and was based on ethnomethodology and symbolic interactionism as theoretical frameworks. The conversation technique was used as a data collection instrument and a discourse analysis was carried out to generate categories a posteriori. The results showed that the students experienced dystopian and utopian elements in their virtual learning process, which influenced their perception and construction of the world. Among the dystopian elements, the economic, social and technological difficulties to access virtual education stand out, as well as the change in the teacher-student relationship that implied greater autonomy and research. Among the utopian elements, the coping strategies developed by the students to manage their emotions and negative thoughts stand out, as well as the change of local-global consciousness that favored their empathy. These findings reveal the importance of promoting the socio-emotional development of students, as well as the proper use of technological tools in normal schools, to improve educational quality and reduce sociales gaps.
The Designing Framework for Flipped Learning Environment on Metaverse to Enhance Mathematical Conceptual Understanding for Seven Grade Students

The purpose of this research was to synthesize the theoretical framework for Flipped Learning Environment on Metaverse to Enhance Mathematical Conceptual Understanding for Seven Grade Students. The target group consisted of three experts reviewing document and designed framework and 29 students in Grade 7, who study in a school in Khon Kaen province. Documentary and survey research were adopted in this study. This research was conducted in four stages: 1) examining and analyzing the principles and theories, 2) reviewing literature, 3) studying relevant contexts, and 4) synthesizing the designing framework for the Flipped Learning Environment. &nbsp;&nbsp;The research instruments were survey a synthesis record of theoretical framework, a synthesis record of design framework, and evaluation form for experts. Data were analyzed by using descriptive and analytical summary interpretation. The results revealed that the theoretical framework consisted of five foundations: 1) Contextual Basic 2) Fundamentals of Learning Psychology 3) Pedagogical Fundamentals&nbsp; 4) Fundamentals of Mathematical Conceptual Understanding 5) media theory and technology base. And the designing framework consisted of four stages: 1) activating of cognitive structure and enhancing mathematical conceptual understanding, 2) promoting cognitive balance 3) enhancing knowledge construction and mathematical conceptual understanding, and 4) supporting knowledge construction. The Flipped Learning Environment was comprised of seven components as following: 1) problem base, 2) resources, 3) related case 4) mathematical conceptual understanding center 5) collaboration 6) scaffolding and 7) coaching.
EdgeActNet: Edge Intelligence-enabled Human Activity Recognition using Radar Point Cloud

Human activity recognition (HAR) has become a research hotspot because of its wide range of application prospects. It has higher requirements for real-time and powerefficient processing. However, a large amount of data transfer between sensors and servers, and computation-intensive recognition models hinder the implementation of real-time HAR systems. Recently, edge computing has been proposed to address this challenge by moving computational and data storage resources to the sensors, rather than depending on a centralized server/cloud. In this paper, we investigated binary neural networks for edge intelligence-enabled HAR using radar point cloud. Point cloud can provide 3-dimensional spatial information, which is helpful to improve recognition accuracy. Time-series point cloud also brings challenges, such as larger data volume, 4-dimensional data processing, and more intensive computation. To tackle these challenges, we adopt the 2-dimensional histograms for point cloud multi-view processing and propose the EdgeActNet, a binary neural network for point cloud-based human activity classification on edge devices. In the evaluation, the EdgeActNet achieved the best results with average accuracies of 97.63% on the MMActivity dataset and 95.03% on the point cloud samples of the DGUHA dataset respectively; and saved 16.9× memory consumption and 11.5× inference time compared to its full-precision version. Our work also is the first to apply 2D histogram-based multi-view representation and BNNs for timeseries point cloud classification.
Explaining Learned Patterns in Deep Learning by Association Rules Mining

This paper proposes a novel approach that combines an association rule algorithm with a deep learning model to enhance the interpretability of prediction outcomes. The study aims to gain insights into the patterns that were learned correctly or incorrectly by the model. To identify these scenarios, an association rule algorithm is applied to extract the patterns learned by the deep learning model. The rules are then analyzed and classified based on specific metrics to draw conclusions about the behavior of the model. We applied this approach to a well-known dataset in various scenarios, such as underfitting and overfitting. The results demonstrate that the combination of the two techniques is highly effective in identifying the patterns learned by the model and analyzing its performance in different scenarios, through error analysis. We suggest that this methodology can enhance the transparency and interpretability of black-box models, thus improving their reliability for real-world applications.
Scrum

The management framework "Scrum" originates from the corporate world of software development and innovation. Based on formalized formats for managing face-to-face communication, team coordination, and process improvement, it has been designed to meet the needs for agile production in an uncertain world where performance criteria, plans and resources may change fast. Although the classic Scrum framework provides clearly structured meeting formats to organize face-to-face communication and artefacts to track and coordinate work progress, current administrative processes, funding and reporting cultures (e.g., strict milestone policies) - and possibly also a distrust of agile methods - have mostly kept Scrum out of academia. Although Scrum was initially developed for software development, Scrum has the potential to address some of the prevalent challenges which transdisciplinary research faces when trying to implement the promotive language of funding applications in practice. In particular Scrum can be adapted to become a tool for creating and maintaining common ground and collaborative accountability among people with various backgrounds and agendas and often diverging perspectives and work habits. Central requirements of transdisciplinary research are outlined as well as the didactic challenges when introducing Scrum to audiences in higher education and how to overcome them. Finally two possible implementations of Scrum in higher education are suggested: "Scrience" for managing transdisciplinary research groups and "EduScrum" for facilitating collaborative and transdisciplinary learning. Both frameworks provide ready-to-implement collaboration and communication structures for interdisciplinary teams, but they may require adjustments to suit specific educational and scholarly needs. Further research and evidence-based consolidation could strengthen the effectiveness of Scrum in academia.
Estimation of Sensor Noise Parameters from Remote Sensing Data Using Convolutional Neural Networks and Mixed Synthetic and Real Data

Characterization of remote sensing (RS) sensors noise is important for optimization and analysis of potential accuracy of subsequent image processing stages (such as filtering or compression, image registration accuracy or objects classification). Blind noise parameters estimation (BNPE) allows analyzing sensor noise directly from noisy images. BNPE is complementary to direct sensor calibration methods and is able to provide additional noise parameters measurements when calibration procedure is not accurate or cannot be performed. Recent BNPE methods show improved performance by utilizing learning-based approach. This paper aims at solving the problem of lack of training data with precise ground truth noise parameters needed for training BNPE models. We focus on learning-based approach using calibrated real data, mixture of synthetic and real data and novel semi-supervised training with uncalibrated real data. The results show that BNPE method training in semi-supervised manner performs better than model-based approach and comparable to supervised training. These results open up possibility of easy extension of training datasets for BNPE methods.
DEVELOPMENT OF MOTORCYCLE SERVICE APPLICATION USING DESIGN THINKING APPROACH AND USER PERSONA

A motorcycle workshop, where regular maintenance and spare part replacements are carried out manually, currently lacks an application. The utilization of a manual system sometimes leads to operational challenges within the workshop, encompassing difficulties in spare part inventory tracking, transaction handling, and report generation. As a response, the author endeavors to develop an application for the motorcycle workshop. The chosen approach involves Design Thinking and user personas, with the aim of identifying core issues and user preferences. This process encompasses five stages: empathize, define, ideate, prototype, and test. The initiative commences with a user persona approach to gain insights into the potential users of the application. The achieved outcomes result in an information system design that can assist the company in addressing issues, such as service data management and service reports that are highly valuable for business development.
Sound Recordings

The current state of audio collecting in libraries is shaped by three interrelated phenomena: the changing media distribution landscape, evolving patron expectations and behaviors, and institutional missions that struggle to strike a balance between preservation and access.None of these phenomena are new to libraries, but the rapid changes of the first two in the recent decade have required libraries to think especially critically about paths forward for collecting media.In this article, we will consider how we got here, survey the current landscape, and provide some thoughts for how we might work as a profession to advance our efforts in media collecting.The Recording Industry Association of America (RIAA) maintains a database called "US Recorded Music Revenues by Format," and it stretches back to 1973. 1 The visualization of this database looks like a series of waves, each representing a sound format entering the market, gaining popularity, only to be overtaken by the next new thing.So it goes with LPs, cassettes, CDs, digital downloads, and streaming services: one after another, each pushing the next format forward. 2 Music sound collections in libraries have followed this wave for many decades, with a slight delay, always a little behind the curve as we adapt to new technologies.Music library professionals now find ourselves in a unique moment within this series of waves, as there is now a significant amount of content that libraries cannot acquire, preserve, or share.This moment in time was telegraphed over a decade ago by D. J. Hoek, in his article "The Download Dilemma." 3 It was already becoming clear in 2009 that music libraries were at a crossroads, as new content was being released on digital platforms intended for individual users, not libraries.
The Role of Narrative Ability on Emergent Literacy Skills and Early Word Reading of Early Childhood Students

Narrative ability is one of the abilities included in emergent literacy and plays a very important role in the development of students' early reading skills. However, research examining the relationship between narrative skills, emergent literacy skills and word reading skills is still limited. Through this research, the researcher investigates the role of narrative ability on emergent literacy ability and reading ability. Besides that, the study investigates the predictive relationship between students' narrative ability, emergent literacy ability, and early word reading ability. The method used in this study was factorial design analysis with several types of data analysis, namely descriptive, correlation, and regression to see the role and relationship of narrative ability, emergent literacy ability, and students' initial word reading ability. Participants in this study were early childhood students, totaling 250 students with an age range of 2-5 years. The research findings show that narrative ability has a significant positive correlation with all aspects of emergent literacy measures. Narrative ability is able to predict the ability to read words in the univariate model. Storybook retelling instructions result in a story that is longer than the original story. This change in story length can have an impact on the use of complex language and decontextualization such as vocabulary development, development of linguistics units, understanding of characters in stories, and story organization. Furthermore, this study also shows that the relationship between students' narrative ability and word reading ability can be mediated by emergent literacy skills, including syntactic abilities, knowledge of letters, phonological abilities, pronunciation of letter sounds, and print conventions. Although the relationship between narrative ability and students' initial reading ability is not direct, this narrative ability makes a significant contribution because narrative ability has a significant impact on emergency literacy skills which, in turn, supports the development of students' reading skills. This research implies that parents or teachers need to consider various alternatives in developing students' reading skills by optimizing narrative skills and other emergency literacy skills so that students are better prepared when they enter school age.
Estágio em Terapia Ocupacional: potencialidades e desafios da telessaúde/ Fieldwork activity in occupational therapy: potential and challenges of telehealth

Contextualização: O presente artigo apresenta e analisa vivências de estágio supervisionado de Terapia Ocupacional em Saúde Mental, realizadas por telessaúde durante a pandemia COVID-19. Processo de Intervenção: As ações apresentadas foram desenvolvidas em um Centro de Atenção Psicossocial tipo I no interior do Ceará, através de videochamadas com duas usuárias, estagiárias e a terapeuta ocupacional do serviço. Análise crítica da prática: O processo de intervenção foi construído em conjunto com as duas mulheres e as estagiárias, que trouxeram para o espaço remoto instrumentos já conhecidos pela Terapia Ocupacional no presencial. Síntese de considerações: Dessa forma, este trabalho pretende abordar os desafios e potencialidades da telessaúde, bem como fomentar seu uso como recurso da Terapia Ocupacional para promover transformações no cotidiano. Palavras-chave: COVID-19. Saúde Mental. Terapia Ocupacional. TelessaúdeAbstract Contextualization: This paper presents and analyzes supervised fieldwork experiences in Occupational Therapy in Mental Health, carried out by telehealth during the COVID-19 pandemic. Intervention Process: The actions presented were developed in a Type I Psychosocial Care Center in Ceará through video calls with two clients, the fieldwork students and the occupational therapist from the service. Critical analysis of practice: The intervention process was collaboratively built with the clients and the students, who used in the remote context instruments already known in face-to-face occupational therapy. Synthesis considerations: This paper aims to address the challenges and potential of telehealth and to encourage its use as a resource of occupational therapy to promote changes in everyday life.Keywords: COVID-19. Mental Health. Occupational Therapy. Telehealth. Resumen Contextualización: Este artículo presenta y analiza las experiencias de práctica profesional supervisadas en Terapia Ocupacional en Salud Mental, realizadas por telehealth durante la pandemia de COVID-19. Proceso de intervención: Las acciones presentadas se desarrollaron en un Centro de Atención Psicosocial tipo I en el interior de Ceará, mediante videollamadas con dos usuarios, aprendices y el terapeuta ocupacional del servicio. Análisis crítico de la práctica: El proceso de intervención se construyó junto a las dos mujeres y las aprendices, quienes llevaron al espacio remoto instrumentos ya conocidos por la Terapia Ocupacional en persona. Resumen de consideraciones: Así, este trabajo tiene como objetivo abordar los desafíos y potenciales de la telesalud, así como promover su uso como recurso de la Terapia Ocupacional para promover cambios en la vida diaria.Palabras clave: COVID-19. Salud Mental. Terapia Ocupacional. Telesalud
FINDING RELATED FORUM POSTS THROUGH TWITTER DATA USING MATCHING ALGORITHM

Forum posts has the specific problem of finding related posts to a post at hand. By considering across the related documents the contents of posts are generally consider are whole. Here similarity process are done between two posts with respective segments and should be of same intention. All posts are generally fragmented in the form of group to attain the goal bunches. Now similarities are generally cross view the forums with sections and that will be of same intention.