Reviewerly/exHarmony huggingface dataset:
Quantifying heavy metal concentrations throughout drainage basins from river sediment mixing

&amp;lt;p&amp;gt;&amp;lt;span&amp;gt;The concentration of elements in river sediments play a fundamental role in determining the &amp;amp;#8216;health&amp;amp;#8217; of rivers. They also contain important information about provenance and geomorphic processes (e.g. mixing). For instance, concentrated heavy metals, such as lead, copper and chromium,&amp;amp;#160;can identify foci of polluting industry and stressed ecosystems. &amp;amp;#160;Attempts to monitor pollution in river sediments and to generate geological baselines are thwarted by the lack of available measurements of sediment geochemistry in higher-order, downstream, river channels. We address that issue by developing forward and inverse methodologies to predict the composition of river sediments throughout drainage basins from small inventories of geochemical measurements (tens of samples). A case study, centered on the River Clyde near Glasgow, Scotland, shows that conservative downstream mixing generates robust and continuous estimates of element concentrations in river sediments. Predicted geochemistry and independent observations match well for elements that have diverse concentrations in source regions (e.g. magnesium). Anthropogenic enrichment of heavy metals along large rivers, compared to geologic baselines generated by mixing &amp;amp;#8216;clean&amp;amp;#8217; source regions, correspond to the Glasgow city area and old mining regions. Continuous predictions of river chemistry are used to identify river reaches where heavy metal concentrations exceed toxic threshold levels.&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt;
THE POWER OF INTELLIGENT CONTENT CURATION AND CONTEXT-BASED DIGITAL LIBRARY CONTENT USAGE FOR RESEARCH AND E-LEARNING (THE CASE OF NATIONAL LIBRARY “IVAN VAZOV” – PLOVDIV, BULGARIA)

Information about the paper titled "THE POWER OF INTELLIGENT CONTENT CURATION AND CONTEXT-BASED DIGITAL LIBRARY CONTENT USAGE FOR RESEARCH AND E-LEARNING (THE CASE OF NATIONAL LIBRARY “IVAN VAZOV” – PLOVDIV, BULGARIA)" at IATED Digital Library
Web-Based Inventory Data Processing Information System At The Regional Development Planning Agency (Bappeda) North Sumatra Province

BAPPEDA of North Sumatra Province is one of the government agencies in charge of carrying out government affairs in the field of regional planning and development. BAPPEDA conducts inventory recording activities that are still manual with the given standardization. Weak supervision has a negative impact on management so that reporting of receipts or expenditures of goods and supervision of the use of goods is hampered. It is necessary to make improvements in the management of government-owned inventories in order to increase the effectiveness and accuracy of better data so that it does not require a long time in the processing process. Departing from these problems, a digitalized information system is needed to record inventory of goods. So, the goods data contained in the agency can be stored in the database to avoid loss and other unwanted things. This system will play a role in the goods inventory process which includes archiving goods data, ongoing goods transactions, and detailed reporting on goods at the agency. Searching data is also easier and faster because officers or employees do not need to look for archives in books or files listing items that have piled up because they can look at the inventory database at the agency. This well-digitized inventory system is expected to assist and improve services at the agency and to carry out better supervision.
KNITTIFY: INTANGIBLE VALUES, PRACTICAL SKILLS. A GAMIFICATION DESIGN APPROACH TO INTER-GENERATIONAL CIRCULAR LEARNING

Traditional teaching methods and models, mainly based on the heritage of the 20th century, are facing a structural crisis in the challenge of an increasingly complex world in which students are being prepared for professions “that do not yet exist”. Moreover, the typical skills of literacy, numeracy, articulacy, and recently introduced graphicacy, seem to be no longer sufficient to transmit a range of intangible knowledge and values once passed on between generations within families and social communities.In particular, some mechanisms of spontaneous transmission of soft skills and “atypical” knowledge seem to lose their effectiveness. From the digital natives to the current alpha generation, the processes and sources of information have migrated predominantly to the digital world, to social networks and virtual communities of interest. The interaction among peers, mediated by ICT platforms and devices, replaces the traditional inter-generational migration of expertise. Digital technologies, which have already been introduced into education and training, thus seem to be one of the possible strategies for offering alternative learning models.The paper presents and discusses this topic from a theoretical-critical perspective as well as through practice-based research, i.e. a case study. It approaches the transmission of intangible knowledge and practical skills through a gamification approach. Traditional and previous generations’ ability is formalised and transposed into a mobile app that uses the typical mechanisms of playful engagement to teach, in this specific case, knitting.Methodologically, the research adopted a human-centered design approach and qualitative methods of analysis and evaluation. In particular, a preliminary online questionnaire was used to understand the context, mechanisms and processes of learning in the field of Cultural & intangible heritage and of the didactic approach that considers technologies and digital design as cognitive and experiential enablers in the acquisition and transmission of knowledge. Personas, scenarios and user journeys have been developed, as well as the design of the process, experience and user interface. The developed interactive prototype has been then evaluated through personas & task-based user testing sessions. Though specifically designed for the world of knitting, the project is nevertheless a repeatable and scalable model, a conceptual and design framework in terms of approaches to learning intangible cultural heritage and practical skills tanks to digital tools to be further explored.
EXTERNAL BARRIERS AFFECTING THE EDUCATION SUCCESS IN RUSSIAN SCHOOLS

E. Benks , B. Ilyukhin , N. Serbina The Russian Presidential Academy of National Economy and Public Administration (RANEPA) (RUSSIAN FEDERATION)
Naive bayes algorithm performance for smartphone sentiment analysis in social media

Indonesia with a population of 250 million is a large market, Millennials tend to be more adaptive to the development of communication technology [1]. There are lot of opportunities that are used by various groups, one of which is the need to use smartphones that can make it easier for people to exchange information [2]. Â The shift in sales of smartphone brands in Indonesia is influenced byÂ massive advertising carried out by smartphone vendors (smartphone capitalists) to consumers [3]. The enthusiasm of the community in welcoming this platform is so great, lot of comment about smartphone brand stated by public is an interesting thing to be processed to be information. Utilization of that information requires analytical techniques so that the produced information can help many parties. The method used in this study is NaÃ¯ve Bayes classification method which is a learning technique for data mining algorithms that uses probability and statistical methods [4]. This method is used to classify comments given by the community to smartphone brands. The comments given in this application will later be classified into positive, negative, and neutral comments. The purpose of this study was to find out how much positive, negative and neutral comments the community gave to smartphone brands, so that later it would facilitate the smartphone brand in providing policies or development in the future.
A Study on Region-Based Image Segmentation Techniques

This paper addresses the comparison of two popular region-based image segmentation techniques namely the Watershed method and the Mean-shift method. The watershed method is a mathematical morphology based image segmentation approach while Mean-shift method is a data-clustering method that searches for the local maximal density points and then groups all the data to the clusters defined by these maximal density points. Here the efficiency of the both segmentation techniques is presented
ON-LINE LEARNING STUDENTS INVOLVEMENT INTO CLASSROOM WORK IN THE CONDITIONS OF HYBRID EDUCATION

T. Bukina 1, L. Malakhova 2, E. Novgorodova 2, E. Nelyubina 3 1Kazan Federal University (RUSSIAN FEDERATION) 2Kazan State Institute of Culture (RUSSIAN FEDERATION) 3Kazan Branch of The Russian State University of Justice (RUSSIAN FEDERATION)
Application of VR characteristics and narrative methods in artistic creation: A case study of “Inori”

The unique environment brought by the immersive virtual space of VR provides artists with new possibilities, new perspectives and creative methods. This is a world beyond the reach of graphic painting. We hope to know whether artists consider the characteristics and narrative methods of VR as necessary elements of their works when creating with VR to think about the existing relationship between display, viewing and being watched. This study took the VR art work “Inori” as the subject of case study. Through qualitative interviews, semi-structured interviews were conducted with the artists of this work, including Miwa Komatsu, Szu-ming Liu, general manager of HTC, Kay Huang, music creator, as well as with the audience. Based on VR 3I (Immersion, Interaction, Imagination) proposed by Burdea and Coiffet (2003) and related literature on VR text narrative methods, this study explores whether such six dimensions as immersion, interactivity, imagination, telepresence, region of interest and guiding the audience's attention are important elements in the artist's creation and influence the artist's performance and the audience's viewing experience. The results are as follows: Miwa Komatsu agrees that the six dimensions have a positive impact on VR art creation; Szu-ming Liu believes that the six dimensions have been taken into consideration in the creation, and they are specially designed for this purpose in the technical aspect; Kay Huang also agrees that VR has these characteristics and is specially designed for music creation; viewers believe that these six dimensions can make people more aware of the creator's creative mood and world than plane art or sculpture.
Distance Learning Technologies during Pandemia: Implementation Approach and Example of Decision Making

The happenings of 2020 were highlighting the topic of the role and place of distant learning in all educational institutions. In close future the transfer to the unified platform inside every institution is unavoidable, but it remains open if the previous experience of the e-learning professionals will be considered. The example described in this article raises doubts about it.
REMOTE TEACHING DURING THE COVID-19 PANDEMIC IN CROATIA: A COMPARISON OF TEACHERS’ EXPERIENCES DEPENDING ON PRIOR SCHOOL PARTICIPATION IN DIGITAL TECHNOLOGIES IMPLEMENTATION PROJECT

Information about the paper titled "REMOTE TEACHING DURING THE COVID-19 PANDEMIC IN CROATIA: A COMPARISON OF TEACHERS’ EXPERIENCES DEPENDING ON PRIOR SCHOOL PARTICIPATION IN DIGITAL TECHNOLOGIES IMPLEMENTATION PROJECT" at IATED Digital Library
IMPROVING TEAMWORK REPORTS QUALITY IN HIGHER EDUCATION USING ICT TOOLS

E. Romero 1, J. Remón 2 1University of Zaragoza (SPAIN) 2Instituto de Carboquímica (ICB). National Spanish Research Council (CSIC) (SPAIN)
Application of Machine Learning Algorithms to Disordered Speech

Aphasia is an acquired neurogenic language/speech disorder that can be assessed with one of the well-known assessment standards, such as the Chinese Rehabilitation Research Center Aphasia Examination (CRRCAE, for Chinese-dialects speaking patients), Aachen Aphasia Test (AAT, for German-speaking patients) and Boston Diagnostic Aphasia Examination (BDAE, for English-speaking patients). These standards are utilized by a skilled speech-language pathologist (SLP) to assess patients with aphasia (PWA). Generally, there are three aphasia assessment tasks where an SLP performs a comprehensive examination of the patient’s communication abilities, including speaking, expressing ideas, understanding language, and reading and writing. These tasks are the discrimination between healthy and aphasic speech, the degree of severity of impairment for aphasic patients’ assessment and the classification of aphasia syndromes (such as Global aphasia, Broca’s aphasia, Wernicke’s aphasia, and amnesic aphasia). Conventional methods of aphasia assessment and rehabilitation are resource-intensive processes that require the presence of an SLP. Due to the vast number of PWAs, the big data involves in the aphasia assessment and the financial difficulties, it is complex to fulfil this requirement manually. Therefore, automation of the aphasia assessment process is essential to attract researchers’ attention. There are several research efforts in automating the aphasia and speech disorder assessment process using machine learning (ML) algorithms. This chapter presents the application of classical machine learning (CML) and deep neural networks (DNN) to aphasic speech assessment. Moreover, the challenges and limitations facing ML algorithms over disordered speech datasets are presented. Furthermore, the chapter provides recommendations on the suitable ML framework for aphasia assessment based on comparative performance results between various CML’s classifiers and CNN algorithm over aphasic speech. This chapter also presents two practical examples of the ML application to aphasia assessment.
TECHNOLOGY OF TEACHING LISTENING

The article discusses the issue of listening, as an independent type of speech activity, and its features in teaching a foreign language. The article provides a unified classification of types, mechanisms, listening difficulties and suggests supports to be used in teaching listening comprehension to students of English, whose mother tongue is Tatar. The method of comparative analysis enabled us to highlight linguistic similarities, which facilitate the perception of information in the target language. The article focuses on the phonetic, grammatical and lexical phenomena with the aim of elaborating a system of learning tasks to develop Tatar students’ comprehension skills. Our goal is to make sure Tatar students of English have a successful experience of listening comprehension despite the difficulties this type of learning activity presents to foreign language learners. The listening process should be systemic, while the relationship between listening and other types of speech activity (reading, writing and speaking) should be taken into account, since the role of listening in the successful mastering of each of the types of speech activity is effective. In the process of studying the topic, the selection of auditory exercises for more effective teaching of listening lessons, it was found that listening, being closely related to other types of speech activity, plays an important role in the study of a foreign language in communicatively directed learning.
A feature extraction method for automatic identification of flying targets from radar data

Flying target identification is an important and challenging problem in airborne surveillance systems. In this report, we propose a method to automatically identify the flying targets by physical information (coordinates, heading, speed), time, and identification information (3/A code). This method includes two steps: features extraction and building a machine learning model. In the features extraction step, features that are extracted include cell indexes corresponding to coordinates, information of flight path, time in day/night format, heading, speed, and 3/A code, constructing n-dimensional vector. This vector is used as input for training a Random Forest model, to automatically identify class labels of flying targets.
Validadion of three Brazilian Global Atmospheric Model experiments (without, fixed and monthly climatological aerosol) against ERA5 and CERES-EBAF

&amp;lt;p&amp;gt;The Sun&amp;amp;#8217;s radiation is the primary energy source for chemical, biological, and physical processes that happen in the climate system. Thus, the earth-atmosphere radiative balance system is one of the main aspects of climate change. Natural fluctuations in incident solar radiation caused by the sunspot cycle can influence the energy balance. In addition, human activities can also affect this balance. Changes in gases and aerosols emissions to the atmosphere can modify its composition because they are involved in complex chemical reactions, such as ozone concentrations. Gases and aerosols can absorb, scatter, and reflect incident solar radiation, thereby affecting the balance. This study assesses the direct impact of aerosol (through changing the optical depth of aerosol-AOD in the radiation subroutine) on the surface atmospheric temperature and radiation balance. Three simple experiments for 1998-2017 were carried out through numerical modeling using BAM-v1.2 (Brazilian Global Atmospheric Model), the operational weather and climate forecasting model at CPTEC/INPE (Center for Weather Forecasting and Climate Studies/National Institute for Space Research). These experiments were zero aerosols, fixed AOD over the land and ocean, and AOD climatology with a spatial and temporal variation (AOD-C). The surface atmospheric temperature was validated against the ERA5 reanalysis from December to February (DJF) and June to August (JJA). Also, the downward shortwave solar radiation on the clear-sky variable was validated against CERES-EBAF satellite data. We performed the bias, the difference between the model and the reanalysis data (ERA5) and EBAF-CERES, correlation and RMSE of the model results against ERA5 and EBAF-CERES for surface temperature and downward shortwave solar radiation on clear-sky respectively. Our results have shown a positive bias atmospheric surface temperature for the northern hemisphere continent and a negative bias for the southern hemisphere continent during JJA. We observed a decrease in this positive bias in the northern hemisphere in the experiments with fixed aerosols, but an important improvement (vies, correlation, and RMSE) was observed in the experiment with AOD-C. On the other hand, during the DJF period, the model has a positive bias only in some continental areas, such as southwestern South America and South Africa, North Africa, and the Australian continent. Similarly, to JJA, we observed improvements in these regions in the experiments that use fixed and AOD-C. The downward shortwave solar radiation on clear-sky results for both DJF and JJA showed an inversion from the positive bias to a negative bias in the model version without aerosols to the model with fixed aerosols and AOD-C, due to the presence of the aerosol, which reduces short wave flow. An important improvement (vies, correlation, and RMSE) in the downward shortwave solar clear sky was observed in the version that uses AOD-C during JJA.&amp;lt;/p&amp;gt;
A New Secret Sharing Scheme Based on Hermite Interpolation and Folded Magic Cube Rules

In this paper, a modern secret sharing scheme has been proposed that deal with set of variables points along specific polynomial. The main idea is to establish the dimension of magic cube into a secret point at a Lagrange polynomial equation. The secret value can be reconstructed from set of cooperated dealers or participants according to predefined threshold. The core idea is how to reconstruct a full magic cube of six dimensions across single key solution. The proposed method adopted Hermite mathematical comprehension that allows minimum number of participants with k-points under definition of a polynomial with degree k – 1 to reconstruct the secret properly. The proposed scheme supposed each dealer has his own share and any group of shareholders at the decided threshold together they can recover the secret. The proposed idea gave a good implementation and fast secret recovery with new mathematical orientation.
SOCIO-PEDAGOGICAL APPROACHES FOR NON-FORMAL EDUCATION OF CHILDREN AND STUDENTS WITH SPECIAL EDUCATIONAL NEEDS

The content of the article examines the problem of non-formal education of children and students with special educational needs in order to their timely and adequate social updating. This type of educational support includes the creation of conditions ensuring the successful integration and realization of public relations by persons in a state of social inequality. In view of the effectiveness of this type of social impact, it is necessary to develop and test approaches and strategies in the field of formal and non-formal education. They should be aimed at the early adequate socialization of adolescent members of society, who due to their social status to a greater or lesser extent are difficult to adapt to its requirements. The article traces the concepts and practical forms for the implementation of pedagogical interaction in the field of non-formal education with children and students with special educational needs. The fundamental initial formulations for its implementation are considered, the specific parameters of interaction are derived, the tendencies and the new challenges in the context of the content, methods, techniques, approaches and forms for organization are outlined. Emphasis is placed on the importance of implementing effective educational support as a key factor for the successful socialization of children and students with special needs. The article presents the specific features of the informal type of educational interactions in the context of the concept of inclusive education. The current criteria and conditions for their effectiveness are also systematized. These include a cluster of professional competencies of specialists - social pedagogues, strategies for the formation of specific key social competencies, the use of technologies that stimulate personal growth and approaches to facilitate adolescents with special educational needs in their adaptation to internal and external changes in social and educational environment.
An Approach to Recognize Handwritten Digits Using Machine Learning Classifiers

Handwritten digit recognition is one of the most important issues in the area of pattern recognition researches. There are many uses of handwritten digit recognition such as Bank check processing, sorting postal mail form, phone number data entry are common applications of automatic digit recognition. The sentiment of the problem deceits within the capability to develop an efficient algorithm that can recognize handwritten digits. Usually, these digits are normally found from scanning documents with digital devices. Typically storing handwritten digits such as phone number, bank account number, postal numbers and so is extremely troublesome with human intervention. An efficient handwritten digit recognition can eradicate this hazard. To eliminate the difficulties of recognizing handwritten digits, this paper proposes an approach using machine learning algorithms. The objective of this research is to present a reliable and effective approach to recognize handwritten digits. Several supervised machine learning classifiers were employed for the recognition and their accuracy are compared and discussed. The highest 97.07% accuracy is found by the Random Forest classifier.