Reviewerly/exHarmony huggingface dataset:
PROFESSIONAL COMPETENCES OF NATURAL SCIENCE TEACHER DISCIPLINES IN THE MODERN SCHOOL

The current situation in education reflects the real picture of the transition to a post-industrial society, the value of which is competence and competence. Until recently, the concept of competence and competence was associated with higher professional education, where specific methods of training specialists were born: task, project, contextual, and others focused on the development of competences and competences of future specialists. Implementation of the competence approach in general education school was engaged and engaged in many scientists-teachers. This approach is a response to the variability of society. The advocates of the competence approach in school education believe that its implementation will allow the creative personality to fill the educational activities of what is learned and overcome the alienation of theoretical knowledge from effective practical realization.The authors pay particular attention to methodological competence as a component of the professional competence of the future teacher of science in the modern school. Teachers' methodological competence is understood as the integral quality of a person, manifested in the ability to pursue activities on the basis of knowledge, skills, values, and experience acquired by future educators in the study of natural sciences, personal attitude to the activity in general and the subject of activity in particular.
Taming the Journal Monster—Building Bibliographical Bridges

The idea of rounding up our special issue in this way came to us while harmonizing all the bibliographical entries into one pattern. We have tried as best as we could to double-check each single source. Sometimes, names that we have never heard before appeared over and over again, in multiple contributions. Somewhere on this planet, different scholars had come across the same readings. We simply wanted to underline this complex, interwoven net of border-crossing–border-creating literature. As editors from different fields, we have learned of many intriguing discourses that were unknown to us before. Quite often, shared literature lists make visible certain symptoms of academic echo chambers, copy-paste works, or self-referencing networks. Shared foundational texts serve as sense-making tool kits to the members of so-called ‘fields’, and give a hint at somehow negotiated vocabulary within them. Yet, what we have in front of us is an example of an interdisciplinary collaboration of writers. Since our special issue had an ‘open call’, many of our collaborators do not even know each other personally. Yet, in the end, it was possible to build bibliographical bridges between all of them—every single contribution has at least one theoretical link to another article. This way, it is possible to theoretically unite our work, and consider it as (part of) a whole.&#x0D; A Meta Bibliography of Some Sort—Bridging MaMo’s BibliographiesIn short, we consider as a bibliographical bridge the shared bibliographical reference to a particular work or to a particular person by at least two of our issue’s authors. If some of our authors refer to ‘writer A’, an imaginary bridge is being created between their contributions—oftentimes unconsciously. These bridges become even more intriguing when noticing that numerous authors independently investigated the identical ‘work B’, without even knowing that another contributor did so as well. Our overview is based on a close examination of all roughly 1000 bibliographical entries in this special issue. It may not be free from errors. For the detailed references, see each contributor’s bibliography individually.
Automatic Feature Extraction from Wearable Sensor Data by Use of Machine Learnings

Feasibility of machine leaning techniques for use of automatic detection and analysis of human behavior has been discussed. We focused on the analysis of swing motions in ping-pong play based on the acceleration sensor data of a Smartwatch and to identify slight difference contained in the motion that is unnoticeable by seeing. It has been discussed the feature extraction ability of PCA and auto encoder based on a multilayered neural network combined with clustering methods and shown the possibility of detection of small scale difference in swing motions.
Enterprise big data analysis using SVM classifier and lexicon dictionary

The emergence of the digital era has led to growth in various types of data in a cloud. In fact, there may be three fourth of the total data will be treated as big data. In many organisations, massive volume of both structured and unstructured data sit idle. Various categories of data are complex for pre-processing, analysing, storing and visualising. Cloud computing provides suitable platform for big data analytics for the storage and for predicting customer behaviour to sell products. Unstructured data like emails, notes, messages, documents, notifications and Twitter comments (including from IoT devices) remains untapped and is not stored in a relational database. Valuable information on pricing, customer behaviour and competitors may be inhumed within unstructured data. This makes cloud-based analytics as an effective research field to address several issues and risks need to be reduced. So we propose a method to extract and cluster sentiment information from various types of unstructured text data from social networks by using SVM classifiers combined with lexicons and machine learning for sentiment analysis of customer behaviour feedback. The method has performed efficient data collection, data loading and efficiently performs sentiment analysis on deep and hidden web.
Fine-grained Type Prediction of Entities using Knowledge Graph Embeddings

Wikipedia is the largest online encyclopedia, which appears in more than 301 different languages, with the English version containing more than 5.9 million articles. However, using Wikipedia means reading it and searching through pages to find the needed information. On the other hand, DBpedia contains the information of Wikipedia in a structured manner, that is easy to reuse. Knowledge bases such as DBpedia and Wikidata have been recognised as the foundation for diverse applications in the field of data mining, information retrieval and natural language processing. A knowledge base describes real-world objects and the interrelations between them as entities and properties. The entities that share common characteristics are associated with a corresponding type. One of the most important pieces of information in knowledge bases is the type of the entities described. However, it has been observed that type information is often noisy or incomplete. In general, there is a need for well-defined type information for the entities of a knowledge base. In this thesis, the task of fine-grained entity typing of entities of a knowledge base, more specifically - DBpedia, is addressed. There are a lot of entities in DBpedia that are not assigned to a fine-grained type information, rather assigned to either coarse-grained type information or to rdf:type owl:Thing. Fine-grained entity typing aims at assigning more specific types, which are more informative than the coarse-grained ones. This thesis explores and evaluates different approaches for type prediction of entities in DBpedia - the unsupervised approach vector similarity using knowledge graph embeddings, as well as the supervised one - CNN classification. Knowledge graph embeddings from the pre-trained RDF2Vec model are used.
Interactive Methods In Developing Young Learners’ Speaking Skills

Teaching young learners is always a challenge and requires new sophisticated approaches and solutions in terms of developing speaking skills. The article aims to analyse the ways interactive technologies influence motivation and encourage young learners to speak fluently. To achieve it, emotional and psychological difficulties students experience are to be taken into consideration. In this respect, IM are vital and need further development to be applied in educational process. To boost students’ speaking skills, to help them overcome psychological barrier a new pattern of teaching-learning process needs to be worked out. The article presents the developed and implemented an interactive activity-based model of speaking practice. For the experimental base of the study two groups of 20 young learners aged 8-10 participated in the experiment. The article describes the results of the experimental study and one of the lesson patterns that was developed by the authors. IM proved to be a very efficient motivating tool to acquire speaking skills in a more student friendly educational environment. The results of the study may be useful for teachers and tutors working with this age group. To achieve success in teaching-learning process a special lesson pattern should be developed. The interactive method-based teaching pattern, suggested in the article, increased young learners’ motivation, broadened their horizon, helped to create comfortable educational environment and resulted in their ability to work independently and think critically.
뇌자동화(brain-on-autopilot) 현상과 예방을 위한 예술감상교육

In this message-saturated world, the transition from a literacy-based culture to a digital one has brought unintended collateral consequences of invention, discovery with convenience, and efficiency. However, it has simultaneously worsened typical spasmodic acts and taken away the importance of the depth of thought processes and time-consuming viewing processes. The digital mode of reading, for temporally greater effectiveness causes brain-on-autopilot and the overabundance of information consequently brings about a scarcity of attention, which is reaching a critical level. These side effects come from the immanent plasticity of human brain. The generation of the age of digital culture does not have a chance to foster their powers of observation and deep-thinking processes and to form and develop their belief systems, which gradually weakens the power of analogous thinking and critical thinking. In this respect, this study examines various theories and practices including those of Maryanne Wolf concerning digital literacy and the brain, Howard Gardner's multiple intelligences, and Abigail Housen's aesthetic developmental stages to demonstrate the impact of education through art appreciation on the promotion of reasoning, analogous and critical thinking skills that require active brains. In conclusion, I suggest timely proper ways of teaching based on art appreciation with an emphasis on the aspect of spatial intelligence and multiplicity in art as a road map for the generations of the digital age.
Exploration on the Construction of Ancient Chinese Database against the Background of Big Data

With the application of big data in various fields, ancient Chinese teaching also introduces relevant concepts and applies them to teaching. This paper elaborates on the exploration of ancient Chinese teaching in the context of big data from two aspects of curriculum introduction and curriculum resources, with the right to make a contribution.
YABANCI DİL OLARAK TÜRKÇE ÖĞRETİMİNDE FORMATİF BİR TEST OLARAK “KAHOOT!” UYGULAMASI

Today traditional tools are mostly used to measure and assess the teaching of foreign languages. However the development of technology makes unavoidable the usage of   online assessment in the measuring and assessing process in education. Thus, this study firstly discusses types of measuring and assessment and then analyses the formative assessment as an assessment type. In this context, we discussed the online application: “Kahoot!” and how it can be used as a formative test for A1 and A2 levels learners in teaching foreign languages. Moreover we evaluated the application provided motivation for the learners in the measuring and assessment process. Utilising the scanning method in the study process, the research made use of foreign studies due to the absebce of domestic related research.
The Trajectories of Teachers Performance Evaluation in High Schools

This research investigated the quality of performance evaluation score. Results showed that teachers performance score varies with where the teacher teaches, who evaluates the teachers and what the teacher is. Some schools give high some give very low points. Students high to male, newer and younger teachers; whereas schools favour male, experienced (long stayed) and older teachers which oppose students’ preference except in gender cases. Self-evaluation and actual performance are poorly correlates. From these results it can be suggested that the purposes of performance evaluation suggested to be linked to schools effectiveness evaluations. Second procedures of performance evaluation administration should be planed. Thirdly evaluators should be accountable for what they did on teacher and continuous training of evaluators of performance is important. Student’s contentment with young and relatively newer teachers may indicate that older and long stayed teachers would be exposed to emotional exhaustion that need experience based sensitization.
UPAYA MENINGKATKAN HASIL BELAJAR PAI SISWA V SD NEGERI 003 TASIK JUANG MELALUI MODEL PEMBELAJARAN GROUP INVESTIGATION

This study aims to improve student learning outcomes of PAI through the Group Investigation learning model. This research is a classroom action research conducted at SDN 003 Tasik Juang. The subjects of this study were 30 people. The research will be carried out from August to September 2019. The research instrument used was an observation sheet and a test of learning outcomes. The results showed an increase in student learning activities and outcomes with a percentage of student activities in the first cycle of 57.5% with enough categories increased to 72.5% with a high category, student learning outcomes in the first cycle showed as many as 17 students or 56.7% who meet the KKM value set with an average learning outcome of 64.5 which is included in the category of being increased in the second cycle which shows as many as 24 students or 80% have met the KKM with an average of 75.3 which is included in the high category. Based on these results it can be concluded that the learning model of Group Investigation can improve the learning outcomes of PAI SDN 003 Tasik Juang students.
NSW Needs a Strong Mandatory Data Breach Scheme: Submission to Inquiry into NSW Adopting a Mandatory Reporting Scheme for Data Breaches

This submission seeks to respond to the questions raised in the call for submissions by the NSW Department of Communities and Justice’s (‘NSW DCJ’) Inquiry into Adopting a Mandatory Reporting Scheme for Data Breaches. As scholars working at the intersection of law and technology, we are delighted to participate in this inquiry led by the NSW DCJ. In this submission, we draw upon some of the research conducted by the Allens Hub researchers to assist the NSW DCJ in their inquiry. We are grateful for the opportunity to present our views and hope this submission will assist this Inquiry. The opinions expressed in this submission are the views of the authors, and do not necessarily reflect or present the views or positions of the Allens Hub or the UNSW Law.
Gerakan literasi sekolah Muhammadiyah untuk majukan bahasa dan Sastra Indonesia

Gerakan Literasi Sekolah (GLS) or School Literacy Movement is being promoted in all schools in Indonesia, including amal usaha Muhammadiyah (AUM). The aim of GLS is to foster interest in reading and writing the teachers and students in school. For that, the teachers and students at AUM, especially in Kabupaten Kebumen or Kebumen Regency, are also expected to play an active role in the success. In the case, GLS AUM is associated with the field of Indonesian language and literature. This program was held on 9 and 10 August 2018. This program was a training program to write fairy tales for TK ‘Aisyiyah Bustanul Athfal (ABA) throughout Kebumen Regency. This training produced 28 fairy tale texts with various themes that would later be published into fairy anthology books. Among them, fairy tales entitled “Elang Bersayap Satu”, “Durian Berkulit Emas”, and “Foto Ajaib Nia”
CNS: CycleGAN-Assisted Neonatal Segmentation Model for Cross-Datasets

Accurate segmentation of neonatal brain MR images is critical for studying early brain development. Recently, supervised learning-based methods, i.e., using convolutional neural networks (CNNs), have been successfully applied to infant brain segmentation. Although these CNN-based methods have achieved reasonable segmentation results on the testing subjects acquired with similar imaging protocol as the training subjects, they are typically not able to produce reasonable results for the testing subjects acquired with different imaging protocols. To address this practical issue, in this paper, we propose leveraging a cycle-consistent generative adversarial network (CycleGAN) to transfer each testing image (of a new dataset/cross-dataset) into the domain of training data, thus obtaining the transferred testing image with similar intensity appearance as the training images. Then, a densely-connected U-Net based segmentation model, which has been trained on the training data, can be utilized to robustly segment each transferred testing image. Experimental results demonstrate the superior performance of our proposed method, over existing methods, on segmenting cross-dataset of neonatal brain MR images.
PROBLEMS OF THE ORGANIZATION OF TRAINING OF STUDENTS OF HIGHER EDUCATION INSTITUTIONS IN MODERN ECONOMIC CONDITIONS

Article is devoted to the organization of training of students of higher education institutions in modern economic conditions. Authors focus attention on what often remains to students not clearly, than the training why it is necessary to participate in it that it gives is good.That is, does not attract the offer of the companies as, as a rule, they standard, boring and imperceptible.The main methods of a researchthe analysis of research literature, methods of the theory of management, the theory of the organization.Following the results of a research authors drew a conclusion that, for the successful organization of training it is necessary to approach how to invite students to a training and as to carry out it creatively.
LibGuides: Course Reserves,Short Loan,Restrict Resources: Course Reserves

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Approximate Semantic Event Processing in Real-time Linked Dataspaces

Within dataspaces, data sources are not necessarily fully integrated or homogeneous in their schematics and semantics. For dataspaces to support a real-time response to situations of interest when a set of events take place, for example from sensor readings, there is a need for a principled approach to tackling data heterogeneity within real-time data processing. In this chapter, we detail techniques for developing dataspace support services for dealing with the semantic heterogeneity of real-time data.
Proposing a Classification Method of Human Behavior Focusing on Orbital Characteristic on Feature Space in a Neural Network

We propose a method using an auto encoder multilayered neural network that can classify and extract small scale difference in human behavior. The video images of ping-pong swing forms were recorded by the high-speed camera and analyzed differences in movement depending on a different cluster obtained by k-means method applied to orbital data in the feature space. We confirmed that the orbits in the feature space represent some kinds of characteristics of swing motions and showed the possibility of automatic detection of human behavior by focusing on orbital features created in the middle layer of an auto encoder neural network.
Digital method for gear measuring data

In order to meet the requirement of short delivery time, high quality, high efficiency and intelligent requirements of the gear industry, this paper presents a standard language GXML (Gear Extensible Markup Language) for gear measuring based on XML. Through the analysis of data characteristics in the whole cycle of gear, GXML is designed to standardize the data in the transmission process of gears. The experimental results showed that the data exchange mode based on GXML and the mapping between GXML documents and databases can achieve cross-platform data transmission, improve the production effectively and reduce production costs.
Performance Evaluation of Vehicle Routing Heuristics

This thesis has researched the automation of performance evaluation of vehicle routing heuristics. The trade-off between solution quality, which is composed of multiple variables, and runtime make performance evaluation challenging. Therefore, it is often done by human experts. The research question of this thesis is: “How can we determine a performance measure that correctly represents the trade off between quality and runtime in vehicle routing heuristics?”. A literature review revealed that much research was done on performance evaluation, but not on heuristics specifically. The performance profile, a cumulative distribution function, is said to reflect all major performance characteristics of a solver. This, combined with a clustering algorithm, is used in this thesis in a classifier to detect performance anomalies. The performance profile needs a performance measure, for which three options were introduced: the area under the chart, the quality at the same time and the maximum difference. Through experimentation, 18 measure configurations were tested and rated on their accuracy and apparent issues. Three of the measure configurations have promising results, with an accuracy of roughly 80%.
Design Space Exploration of the AES Encryption Algorithm Implementation for Securing CAN Protocol

IoT technology is growing very fast and one of the requirements of this technology is integrating different communications protocols and networks. In an IoT network, security of such a heterogeneous and large network is very important. Transport systems are part of this super network and in-vehicle protocols are used in such systems. Unfortunately, the Controller Area Network (CAN) protocol, the most popular protocol in the systems, designed without security in mind. In this paper, the Advanced Encryption Standard (AES), an encryption algorithm, is used to prevent masquerade and replay attacks in order to secure CAN protocol to an appropriate level. The paper has a plan to explore for an efficient implementation of AES encryption algorithm for the communication protocol. These implementations have been evaluated on an FPGA ML605 development board. The best implementation of the AES among 8-, 16-, 32- and 64-bit data paths has been investigated. The most important criteria for the protocol in these AES designs are such as consumed power, area, and cost in addition to providing better throughput. The 64-bit structure of the designed AES is selected which has the frequency of 21.4 MHz, significant throughput of 412.39 Mbps, reasonable area of 784 slice on Spartan III FPGA.
Application of continuous wavelet transforms for swell noise attenuation

Ocean-surface related noises known as swell noises are a common occurrence in marine surveys and present a challenge for traditional noise suppression techniques, due to the non-random nature of the events.In order to identify this type of noises, we can use differences between real and modeled data sets.This is particularly useful in the context of full waveform inversion, where both types of data are available.Here, we apply a continuous wavelet transform (CWT) to real and modeled data to attenuate swell noise events by estimating filters from the modeled data using a smooth velocity model and applying those to the real data.We show that filters using the CWT domain can efficiently attenuate swell noise by correctly estimating the time windows and wavelet scales of desired data.