Reviewerly/exHarmony huggingface dataset:
Ecosistema de Hardware y Software para la introducción de la robótica a niños en etapa escolar

espanolLa investigacion tuvo como objetivo el desarrollo de un ecosistema de hardware y software, con el fin de introducir los conocimientos de la robotica a los ninos en etapa escolar a traves de una aplicacion local y su prototipo. El sistema en su totalidad tiene como finalidad mejorar la manera en la que se le presenta la tecnologia a los ninos, ya queel mismo provee funciones que facilitan el entendimiento de distintas areas tecnologicas,puesto queademas de poder observar el funcionamiento de un robot, estos podran tambien programarlo de manera que el robot realice las funciones que ellos deseen. El sistema esta basado en la plataforma RaspberryPi, y con el funcionan un conjunto de modulos que permiten su funcionamiento, como lo son el modulo de computos proporcionado por el RaspberryPi, ya que el mismo se conecta a la aplicacion la cual vendria siendo el modulo de software y un modulo de componentes electronicos queseria el prototipo como tal. Se baso en autores como Arias, F. (2006), Hernandez, R., Fernandez, C. yBaptista, P. (2014), Hurtado, J. (2010), IBM (2014), Oracle (2018), Bernal (2020)ySabino (2007)parael nivel, diseno y unidad de analisis de la presente investigacion. Se utilizaron lenguajes como Python para la programacion del RaspberryPi y del servidor. Javascript y HTML para la aplicacion local. Se cumplio en su totalidad con los objetivos de la investigacion. Conlos resultadosobtenidoslos investigadores comprobaron que,si se imparten los conocimientos del area robotica a los ninos atraves de sistemas,se mejora el aprendizaje y la calidad de educacion tecnologica impartida EnglishThe research aimed at the development of a hardware and software ecosystem, in order to introduce the knowledge of robotics to school children through a local application and its prototype. The system as a whole aims to improve the way in which technology is presented to children, since it provides functions that facilitate the understanding of different technological areas, since, in addition to being able to observe the operation of a robot, they can also program it so that the robot performs the functions they want. The system is based on the RaspberryPi platform, and with it work a set of modules that allow its operation, such as the computation module provided by the RaspberryPi, since it connects to the application which would be the module of software and an electronic component module which would be the prototype as such. Authors such as Arias, F. (2006), Hernandez, R., Fernandez, C. and Baptista, P.(2014), Hurtado, J. (2010), IBM (2014), Oracle(2018), Bernal (2020)and Sabino (2007)were based on the theoretical part for the level, design and unit of analysis of the present investigation. Languages such as Python were used for RaspberryPi and server programming. Javascript and HTML for the local application. The objectives of the research were fully met, with these results the researchers verified that if knowledge of the robotics area is imparted to children through systems, learning and the quality of technological education are improved
Jazz in Worship and Worship in Jazz: Exploring the musical language of Liturgical, Sacred, and Spiritual Jazz in a Postsecular Age

Faculty opponent: Melvin L Butler, PhD, professor in music, University of Miami, Florida, USA. For sounding music see Research Catalogue Exposition available at:Uwe Steinmetz, ‘Jazz in Worship and Worship in Jazz‘, Research Catalogue (2021)https://www.researchcatalogue.net/view/1216772/1216773/0/0The public defences take place virtually via ZoomDue to restrictions in connection with COVID-19, the public defences take place using a video link (the Zoom webinar tool), where participants need access to a computer and a network. All participants will be given the opportunity to ask questions at the end of the public defence, via Zoom. Video link will be available from 9 June 2021 at this page: https://www.gu.se/evenemang/disputation-uwe-steinmetz-musikalisk-gestaltning
Aprendizajes, sujetos y pandemia: algunas reflexiones desde la Psicopedagogía

In this writing, some considerations are presented regarding the effects of the pandemic in terms of learning in the subjects that travel through schools. In this sense, substantive questions will be raised that invite us to reflect on the consequences in education, in the school experience and in the positions of those who make up the educational institutions produced by the confinement in the framework of COVID-19.Taking as references the current contributions on the subject, complemented by classic authors who have made their contributions on institutions, teachers and learners, we will seek to think about the current situation in a psychopedagogical key inviting the reader to think about possible alternative scenarios.
An Efficient Algorithm to Identify Best Detector and Descriptor Pair for Image Classification Using Bag of Visual Words

Object identification and classification are important application in the computer vision and image processing domain. In this work, an attempt has been made to analyze various detectors and descriptors for extracting the best features and using bag of visual words (BoVW) for object classification. Experiments have been conducted on three significant different datasets COIL 100, CALTECH 101 and WANG. Features extracted from various detectors and descriptors have been used for classifying the images based on the objects. The best detector descriptor (FAST-SIFT) and optimum cluster size have been empirically determined to achieve high classification accuracy. The results obtained are used for performing further object retrieval.
Big Data Processing with Balanced Resource Utilization

Due to huge increase in generation of data with each day, the collection and analysis of data has become a major research area today. Big Data analytics helps the organizations to utilize this voluminous amount of data and infer useful information to improve decision making process. To perform Big Data analytics, Hadoop framework is widely used to manage distributed storage and processing of Big Data. Due to its mechanism of distribution of the data and code across multiple nodes/VMs, it has introduced the challenges in data movement and load balancing among DataNodes. While analysing Big Data using Hadoop, the random placement of data blocks may result in imbalance of data across DataNodes which leads to poor performance of the system. To address these issues, this paper proposes a load balancing model, which adaptively balances the data on each DataNode/virtual machine. The proposed algorithm takes into account the current state of the each virtual machine(VM) based on two parameters i.e. current memory utilization & CPU utilization. While each data chunk is processed by one of the VMs, the load status of each VM is monitored by evaluating the current load on each VM and the load is migrated accordingly from overloaded to least loaded machine to achieve balanced resource utilization. The main objective of the proposed technique is to increase overall performance of the system.
A Trusted New Method for Authentication and Security for Web Applications in Cloud Using RSA Algorithm

Cloud stands for Common Location independent Online Utility on Demand services (or) Communities Libraries, Online Union Database which is abbreviated from AT&T (American Telephone & Telegraph) corporation. Now a day’s cloud computing is one of the outstanding generation to provide wide form of services consisting of Software-as-a-Service, Infrastructures-a-Service, Platform-as-a-Service, Data-as-a-Service and Voice-as-a-Service and many others. Cloud computing is a brand new innovated technology which offers various competencies to the users on call for foundation. In cloud computing facts storage is one of the famous offerings which stores records at remote servers and decreases cost at client aspect. Apart from the blessings cloud also lagging in presenting authentication, safety, integrity, availability to the person’s information due to information isn't always beneath control of end user. Secret word and short message based validation strategies are at present the most famous ones to confirm portable clients. Be that as it may, there is numerous security dangers associated with these verification techniques. In this paper, proposed a Novel verification based on multifactor parameters strategy.
LeDoCl : A Semantic Model for Legal Documents Classification using Ensemble Methods

NLP is one of the components of Machine Learning. Topic Modeling is a sub component of information retrieval Information Retrieval is a broad domain research in Natural Language Processing (NLP). This downside has been broadly studied in the perspective of cluster algorithms like K–means and K-fold, that tends to converge to at least one of diverse native issue counting on the selection of format method. To overcome the instabilities and assumptions in existing systems such as Vector Space Model (VSM) and SVD, Semantic based topic modeling (SLDA) and ensemble model with generation and integration is proposed. In the case of topic modelling, instability is visible in two distinct aspects. First, when the topic descriptors are examined over multiple runs. During which there will be considerable change in the term rankings and few terms may appear or disappear completely as well. Next, there could be instability due to the extent to which topics have association with document, through several executions. In the proposed system, ensemble learning comprises of algorithms Kernel Support Vector Machine (KSVM) and Random Forest algorithm which overcomes the instability. The first issue of appearance and disappearance of words between multiple runs is overcome by Gibbs Sampling based Semantic LDA (GSLDA). The second issue of alignment of topics with document is aided by using ESLDA. This ensemble SLDA algorithm show increased accuracy in terms of retrieval and reduced time interval compared to conventional models. The accuracy increases up to 98% using ESLDA compared to SLDA (82%) and term frequency methods (78%).
Socrative, google forms y examtime como métodos de evaluación online

espanolLa aparicion del Covid-19 y el posterior confinamiento han llevado a los docentes a la necesidad de sustituir el tradicional metodo de evaluacion basado en la presencialidad por otros mas modernos e innovadores realizados a traves de internet, entre ellos, los siguientes: Socrative, Google forms y Examtime, objeto de la presente comunicacion y que ofrecen numerosas ventajas no solo para los profesores, sino, tambien, para los alumnos. EnglishThe appearance of Covid-19 and the subsequent confinement have led teachers to the need to replace the traditional assessment method based on face-to-face with other more modern and innovative ones carried out through the internet, including the following: socrative, Google forms and examtime , which is the subject of this communication, which offer numerous advantages not only for teachers, but also for students.
Lessons learned from librarian support in a pandemic: identifying how online discussion boards may augment digital connections

The rapid transition from face‐to‐face tutorials to fully remote digital content delivery in response to the COVID‐19 pandemic has presented challenges and opportunities for student engagement and high‐quality learning and teaching experiences. Google Analytics data identified a 265% increase in access and use (number of sessions recorded) of the online Guide to Discussion Boards (Douglas et al., 2017); indicating increased digital tool use. A sub‐set of Google Analytics data collected from March to August in 2019 and 2020 for the Guide, indicated 483 users in 2019 compared to 1134 users in 2020, and 88% of users in 2020 were identified as new users of the Guide. Concurrently, reflections by educators involved in updating the Guide found the demand for library research assistance increased and diversified during the pandemic. Rapid improvements in facilitation technology, such as Zoom, enabled students to meet librarians anywhere, anytime. A surge in requests for increased online support including synchronous presentations, recordings, and follow‐up drop‐ins was noted, and asynchronous discussions embedded within units increased in use. Small group face‐to‐face workshops became webinars attended by 100 or more students and a greater expectation for 1:1 student support was observed. In response to the identified need regarding librarian support and their involvement in specific unit discussion boards, a new chapter in the Guide will be developed. A section on partnerships with librarians is a logical step to support digital communication in online learning and teaching.
Inter-urban library as a service center for specialists of the agro-industrial complex

Abstract The article is devoted to the research of the inter-urban library role as a center for individual and mass library-information services for specialists in the agro-industrial complex. The work experience of the Volgograd region with agricultural literature is presented and the ways to overcome the problematic field of documentary funds replenishment, the information technologies usage in the technological processes of inter-urban libraries, and the service system management in the region are outlined.
Differential Diagnosis in Late Onset Multiple Sclerosis (P1.2-060)

Objective: To identify clinical-radiological characteristics of patients consulting with suspected Late Onset Multiple Sclerosis (LOMS). Background: LOMS is defined by clinical presentation after 50 years of age, being less than 12% of MS population. Diagnosis is challenging considering the broad spectrum of differential diagnoses proposed for white matter lesions in this subgroup of patients; thus, misdiagnosis is frequent. Finally, there is scarce evidence about prognosis and treatment of these patients. Design/Methods: Patients presenting first symptoms after 50 years of age, consulting in a tertiary neurological center in Buenos Aires, Argentina, from January/2011 to September/2018 referred with previous diagnosis of MS, white matter lesions or demyelinating disorders, were included. Demographic, clinical MRI and oligoclonal-bands (OCB) characteristics were analyzed with parametric and non-parametric tests. Results: We included 153 patients with late onset symptoms: 85 were MS and 67 had other differential diagnosis. The most frequent diagnosis was demyelinating disorders not MS or NMOSD (n=30), followed by microvascular damage due to unspecific white matter lesions (n=25). 26 patients (36%) were previously misdiagnosed with MS diagnosis (not fulfilling MS criteria) and 7 patients were already on disease modifying drugs. The cost of mistreated patients was estimated in USD 7.184.200. Among the patients who met criteria for the diagnosis of LOMS myelitis was the most frequent presentation (37%). On MRI analysis, corpus callosum lesions and periventricular demyelinating plaques (“Dawsonfinger signs supported MS diagnosis”) were the only specific findings bringing statistically significant information to differentiate MS from other diagnosis. Positive OCB were useful to differentiate demyelinating disorders from non-demyelinating etiologies. Conclusions: LOMS diagnosis is challenging, being necessary a detailed clinical history, physical exam and MRI description, in order to avoid misdiagnosis and unnecessary treatment. This is the largest LOMS specific case series from Latin-America, bringing important information about this subgroup of patients, applicability of MS diagnostic criteria and differential diagnosis. Disclosure: Dr. Yorio has nothing to disclose. Dr. Marrodan has nothing to disclose. Dr. Farez has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with TEVA, Merck-Serono, Biogen-Idec, and Novartis. Dr. Correale has received personal compensation for consulting, serving on a scientific advisory board, speaking, or other activities with Biogen Argentina, Teva Argentina, Novartis Argentina and MERCK Argentina, and Merck/Serono Argentina and Novartis Argentina.
Mobile Application for Recording the Results of Laboratory Research of a Synthetic Chemist

This article discusses an application for mobile devices with the Android operating system that allows you to record the results of laboratory research of a synthetic chemist. An overview of the basic functionality of the Chemical Notes mobile application is presented.
Educational technlogies in the process of teaching in a higher education institution

The article describes educational technologies applied in practice. Educational technology is a classic example of social technology and represents a relatively new trend in educational science. Educational technologies are associated with increasing the effectiveness of training and education and are aimed at the final result of the educational process-the training of highly qualified specialists.
Continual Learning in the Teacher-Student Setup: Impact of Task Similarity

Continual learning-the ability to learn many tasks in sequence-is critical for artificial learning systems. Yet standard training methods for deep networks often suffer from catastrophic forgetting, where learning new tasks erases knowledge of earlier tasks. While catastrophic forgetting labels the problem, the theoretical reasons for interference between tasks remain unclear. Here, we attempt to narrow this gap between theory and practice by studying continual learning in the teacher-student setup. We extend previous analytical work on two-layer networks in the teacher-student setup to multiple teachers. Using each teacher to represent a different task, we investigate how the relationship between teachers affects the amount of forgetting and transfer exhibited by the student when the task switches. In line with recent work, we find that when tasks depend on similar features, intermediate task similarity leads to greatest forgetting. However, feature similarity is only one way in which tasks may be related. The teacher-student approach allows us to disentangle task similarity at the level of readouts (hidden-to-output weights) and features (input-to-hidden weights). We find a complex interplay between both types of similarity, initial transfer/forgetting rates, maximum transfer/forgetting, and long-term transfer/forgetting. Together, these results help illuminate the diverse factors contributing to catastrophic forgetting.
MmgCore API Introduction

Part 2 of this book contains a comprehensive review of the game engine’s runtime code. This code exists in both Java and C# and is included in the main project under the MmgCore package, or namespace if you’re following along in C#. The MmgCore API is responsible for handling command-line arguments, processing game engine config files, creating the game’s window, routing input, managing game screens, and much, much more.
IMPLEMENTATION OF CLASSIC POETRY LEARNING VIDEO IN CHINESE LITERATURE

This study aims to determine the increase in the understanding of the students about classical Chinese poetry with and without learning videos of Chinese literature. The implementation of this video is expected to make the learning process easier for the students to understand the meaning contained in classical poetry. This study used an experimental method with the static group pretest and posttest design, using tests as means of collecting research data. The population in this study were students of class A and B of Chinese Language Education of 2019, in total of 52 students. Sampling was carried out randomly with a non-random sampling method, which two experimental groups class A and class B. Class A studied Poetry 1 entitled 春夜喜雨 and class B studied Poetry 2 entitled 春晓. The results showed that understanding of the students about Poetry 1 increased 58.94%, while the understanding of the students about Poetry 2 also increased 36.21%. Referring to these results, it can be concluded that with the learning videos students can be more easily understand the implicit meaning of classical Chinese poetry.
Information technologies in teaching physics in a technical higher education institution

The article discusses current issues related to the methodology of teaching physics in technical universities. The prospects of information technology in the modernization of the educational process in physics, as well as in solving a number of methodological problems were discussed.
Optimization and Embedded Implementation of Gesture Recognition Algorithm Based on Convolutional Neural Network

With the rapid development of information technology and the maturity of computer vision technology, the application of gesture recognition based on vision has gradually become an important research direction in the field of artificial intelligence. As a very natural way of semantic expression, gesture plays an important role in human–computer interaction. However, complex gesture structure and changeable environment increase the difficulty of gesture recognition, resulting in low recognition rate. Convolutional neural network (CNN) improves the problem of manual feature selection in traditional recognition methods, and has been widely used in video monitoring, human–computer interaction, big data analysis and other fields. The real-time requirement of algorithm implementation in these fields is also higher and higher, which makes it very important to study how to use FPGA to accelerate CNN algorithm. Therefore, combined with gesture recognition technology, this paper studies the embedded implementation of convolutional neural network in ZC706 platform.
A survey on problems faced by researchers with English language while writing a research paper

Li, F., Ren, J., &amp; Zhao, H. (2016) To determine the difficulties of students in writing skills, the author conducted a survey on English writing skills and related issues. The majority of students study for academic purposes only, not for future growth. Before guiding students, teachers should gain a thorough understanding of writing skills. What role do grammatical errors such as sentence structure, tenses, modern verbs, passive and active forms perform in reducing cultivates in writing skills? Nishanthi, R. (2018).
Using Artificial Neural Networks to Model Errors in Biochemical Manipulation of DNA Molecules

In recent years, the non-biological applications of DNA molecules have made considerable progress; most of these applications were performed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> , involving biochemical operations such as synthesis, amplification and sequencing. Because errors may occur with specific sequence patterns or experimental instruments, these biochemical operations are not completely reliable. Modeling errors in these biochemical procedures is an interesting research topic. For example, researchers have proposed several methods to avoid the known vulnerable sequence patterns in the study of storing binary information in DNA molecules. However, there are few end-to-end methods to evaluate these biochemical errors with regard to the DNA sequences. In this article, based on the data generated by a DNA storage research, we use artificial neural networks to predict whether a DNA sequence tends to cause errors in biochemical operations. Through comparative experiments and hyperparameter optimization, we analyze the known and potential problems in the research process. As a result, an end-to-end method to model the biochemical errors of DNA molecules <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vitro</i> through a computer system is proposed.