Reviewerly/exHarmony huggingface dataset:
A CASE STUDY OF STUDENT LEARNING DIFFICULTIES ON SOCIAL STUDIES LEARNING IN CLASS V SDN 11 RIO PAKAVA DURING THE COVID-19 PANDEMIC

The purpose of this research is to reveal the factors that cause students to have learning difficulties in social studies learning as well as to find out the teacher's efforts in overcoming students who have learning difficulties in social studies learning. This research is a case study descriptive research and is located in the fifth grade of SDN 11 Rio Pakava. The results showed that the causes of student learning difficulties were the lack of teacher treatment in providing reading materials on social studies subjects, the lack of use of social studies learning media, and lack of parental attention if the students got low grades, readiness, interest, intelligence of students in following subjects. Social studies lessons, and physical disabilities suffered by students and Efforts made by teachers to overcome learning difficulties, namely conducting learning using learning models, using image media, providing additional lessons according to the subject in question, giving homework and remedial teaching.
Nota sulla nozione di dialetto in Cesarotti e nel Settecento italiano

This article proposes a semantic and functional analysis of the notion of dialect in several 18 th century authors. The main focus is on Melchiorre Cesarotti; the analysis also extends to other key theorists in the Italian linguistic debate, such as Muratori, Baretti, Alberti di Villanuova and Denina. With the exception of Denina, dialects appear to be conceptualised by these authors not as separate glottological units but as modalities, or internal varieties, of a roof-language, whose identity is understood as relying on a set of linguistic features and lexical items that are supposed to be common to all Italian dialects since their origins in the Early Middle Ages. This is a schema that is essentially different from modern ideas of the relationship between dialects and a roof-language like Italian.
Imperfections of Scalar Approximation in Calibration of Computer-Generated Holograms for Optical Surface Measurements

Computer-generated hologram (CGH) null correctors are used as accuracy standards for interferometric measurements of optical surfaces and optical systems. Diffractive optics calibrators (DOCs) have been developed to evaluate the phase tolerance of CGHs based on scalar approximation by measuring variations in duty cycle and etching depth. However, if the grating period of a CGH &lt; 5λ, the scalar approximation is not accurate for phase analysis and reconstruction. In this study, the measurement errors of DOCs with small-period CGHs were investigated and experimentally verified. Results show that the imperfections of scalar approximation in CGHs cannot be ignored and the development of rigorous evaluation methods to improve the measurement accuracy of CGHs is of great practical significance.
Approaches to the integration of TRUST and FAIR principles

Work performed in the framework of FAIR4Health project, with funding from the European Union’s Horizon 2020 programme under grant agreement number 824666. In addition, work presented in this paper has been partially supported by the Generalitat de Catalunya (2017 SGR 1749).
Use of Video Method in Teaching Computer-oriented Disciplines

The purpose of the article is to find new methods and means of teaching computer science The research methodology consists of system analysis and classification of demonstration teaching methods. The novelty of the study is the use of screencasting when creating an educational video channel for teaching computer disciplines (Davletkaliev, 2008). Conclusions. In this work, on the example of creating an educational Internet channel, the possibility of increasing the effectiveness of using the video method in the process of teaching computer-oriented disciplines is shown.
The Impact of Technology Adoption on Organizational Productivity

Purpose: This research investigates the impact of technology adoption on organisation productivity. The framework has three independent variables viz. technological change, information technology (IT) infrastructure, and IT knowledge management and one dependent variable as organisational productivity. Research design, data and methodology: An explanatory research design with a quantitative research method was employed, and data was collected using a self-administered questionnaire using online as well as an offline survey. The sample consisted of 300 IT managers and senior-level executives (production as well as service team) in leading IT companies in Malaysia selected using snowball sampling. Normality and reliability assessment was performed in the first stage utilizing SPSS 22, and Confirmatory Factory Analysis (CFA) was performed with maximum likelihood estimation to assess the internal consistency, convergent validity, and discriminant validity. Finally, Structural Equation Model (SEM) and path analysis are conducted using AMOS 22. Results: The research findings demonstrated that technological change and IT infrastructure positively and significantly impact the organisation's productivity while IT knowledge management has significant but negative impact on organizational productivity of IT companies in Malaysia. Conclusion: The research concludes that all three factors plays important role in deciding organizational productivity. Recommendations, implications, limitations and future research avenues are discussed.
N-Gram Fuzzy Keyword Search on Encrypted User Data in Cloud Using Jaccard Calculation

Now-a-days users mostly store their personal data and professional data on the cloud. As a result, there is massive increase in the storage and computing requirements of users. Every time, the data is getting transferred to the remote server in larger chunks, without analyzing whether the server on which the data is outsourced, is a trusted server or not. But the fact is, after outsourcing the data, users are at great security risk factor that tends to lose the local possession of their large size of data. So, to maintain the privacy of personal data/documents stored in cloud environment, it should first get encrypted before outsourcing to the cloud server. After the data is placed on the cloud, retrieving the same data becomes quiet a tedious job. Thus, to retrieve the data several approaches are available in which keyword enabled search of the encrypted data is one of the outstanding techniques. Most of these approaches are only limited to handle a single keyword search with its own limitations. To enhance the searching method in terms of efficiency and speed, a fuzzy multi-key word search technique can be used to retrieve a corresponding document from cloud. The scheme of fuzzy keyword search remarkably improves the system efficiency and security over the cloud environment. The proposed scheme is convenient , manageable, and even requires less resource. The outcomes of this scheme are valid enough to get the accurate files or the closet possible match files searched by the user. Thus, we have proposed a secure search scheme supporting N-Gram fuzzy multi-keyword search over encrypted cloud data.
Blockchain technology for digitalization of the pharmaceutical sector of the Russian Federation

One of the main priorities of the modern healthcare system is the transportation of pharmaceutical products. The drug supply chain consists of many participants. These are drug manufacturers, intermediary organizations, and end users. The biggest problems associated with this transportation are temperature monitoring and the quality of the offered products. This is because many drugs and vaccines remain viable within a certain temperature range. As soon as the temperature regime during transportation is violated, the quality of the medicine decreases sharply. In this article, the author proposes the use of Blockchain technology to solve these problems and focuses on improving the transportation process. In his opinion, a decentralized system based on Blockchain technology is the best technological solution. In addition, the author is developing a concept for the application of Blockchain technologies to create a functioning medical ecosystem.
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Welcome new and incoming students! Learn about the IU Libraries and all that we can do to help you during your time as a student at IUB. Complete this quiz to receive your free cookie.
Harmonious personality development in the context of digital educational platforms

Due to the pandemic, the society has appreciated high technology, which has provided invaluable assistance in the smooth training of personnel. The demand for high-quality, inclusive, accessible digital education has been formulated in all European countries as well as in Russia. Priorities were identified in the creation of a digital educational ecosystem and the formation of digital skills of ecosystem participants for successful digital transformation. In the modern literature one can find the arguments in favor of the presence of a positive or negative relationship between learning in the conditions of digital educational platforms and the formation of the personality of students. Based on the stated views of the personality development in a digital environment, in this study we understand a harmoniously developed personality as a person who is ready to integrate into the world and national culture, who has digital competencies and is aware of responsibility for his professional behavior, as well as striving for self-realization in the modern digital professional space. A system of a harmoniously developed personality formation in the digital educational platform has been developed.
Life, Knowledge and Values: A Tribute to John Stewart

Abstract: John Stewart passed away earlier this year. In this tribute, I present some elements of his biography and of his main intellectual engagements. Keywords: Autopoiesis, cognitive science, …
FACTORS OF STUDENT LEARNING DIFFICULTIES INVERTEBRATES MATTER IN CLASS X IPA SMA NEGERI 3 RANTAU UTARA

This study aims to determine the learning difficulties of students in invertebrate material in class X cognitive aspects, learning indicators, and factors causing students learning difficulties. The method used in this research is quantitative descriptive. The population in this study were all students of class X IPA of SMA Negeri 3 Rantau Utara in the 2017/2018 study year. The research sample was taken by total sampling. This research instrument using test questions and questionnaires. The results showed students have difficulty learning in invertebrate material on the cognitive aspects of C1 (43%) included in the high category, C2 (36.96%) included in the high category, C3 (31.16%) included in the moderate category, C4 (55.37% ) included in the very high category, C5 (47.11%) was in the very high category and C6 (36.23%) was in the high category. In the 1st learning indicator students experience learning difficulties (40.22%) included in the high category, the 2nd learning indicator (55.56%) included in the very high category, the 3rd learning indicator (38.89%) included in the high category , the 4th learning indicator (23.19%) was included in the medium category and the 5th learning indicator (46.09%) was in the very high category. Factors that are quite influential in learning difficulties by students of class X IPA of SMA Negeri 3 Rantau Utara in the 2017/2018 academic year are interest, motivation, and subject matter. Other factors such as intelligence, parents (family), class conditions, school and environment outside the family are in the weak category of influence on learning difficulties. Health factors and teachers are in the category of very weak influence on learning difficulties.
Mixture density network estimation of continuous variable maximum likelihood using discrete training samples

Abstract Mixture density networks (MDNs) can be used to generate posterior density functions of model parameters $$\varvec{\theta }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>θ</mml:mi> </mml:mrow> </mml:math> given a set of observables $${\mathbf {x}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>x</mml:mi> </mml:math> . In some applications, training data are available only for discrete values of a continuous parameter $$\varvec{\theta }$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>θ</mml:mi> </mml:mrow> </mml:math> . In such situations, a number of performance-limiting issues arise which can result in biased estimates. We demonstrate the usage of MDNs for parameter estimation, discuss the origins of the biases, and propose a corrective method for each issue.
An Approach for Sentiment Analysis of Customer Review Data

Sentiment analysis is more promising tool to select the best product based on the customer reviews. The increase in number of websites and brands who are advertising their products leads to increase of customer reviews day by day. Manually it is not feasible to analyze and decide the opinion against a product using those huge reviews. Sentiment analysis automates the process of classifying the products as positive, negative and neutral based on customer reviews. This paper focus on performing sentiment analysis on the text data that contains the customer reviews to obtain the sentiment i.e., opinion of the user about the product from the reviews that the customer have given. This paper also presents the classification of sentiment analysis techniques and stages in sentiment analysis. The approach used in this paper uses both lexicon based technique and machine learning technique, especially SVM. Performance of our proposed approach is evaluated using precision, recall and F1-score. The accuracy of different decisions is also calculated. We used kaggle dataset for the experimenting our proposed sentiment analysis approach.
Automating Induction by Reflection

Despite recent advances in automating theorem proving in full first-order theories, inductive reasoning still poses a serious challenge to state-of-the-art theorem provers. The reason for that is that in first-order logic induction requires an infinite number of axioms, which is not a feasible input to a computer-aided theorem prover requiring a finite input. Mathematical practice is to specify these infinite sets of axioms as axiom schemes. Unfortunately these schematic definitions cannot be formalized in first-order logic, and therefore not supported as inputs for first-order theorem provers. In this work we introduce a new method, inspired by the field of axiomatic theories of truth, that allows to express schematic inductive definitions, in the standard syntax of multi-sorted first-order logic. Further we test the practical feasibility of the method with state-of-the-art theorem provers, comparing it to solvers' native techniques for handling induction.
How to Install BlueStacks 4 on PC/Mac in 2020 (Official Latest)

Bluestacks - an Android emulator that allows its users to run Android apps and games on Windows Computers. Some people need it as a temporary Android ...
MENINGKATKAN KEMAMPUAN MEMBACA PERMULAAN MELALUI MEDIA GAMBAR BERSERI PADA ANAK KELOMPOK A TK BUNGONG NANGGROE KECAMATAN PADANG TIJI KAB. PIDIE

Series pictures are pictures that make up a series of stories. Serial image media is a number of images where one image to another is interrelated and forms a specific story line. Reading the beginning is a skill and cognitive process. The skill process refers to the recognition and mastery of phoneme symbols, while the cognitive process refers to the use of familiar phoneme symbols to understand the meaning of a word or sentence. The formulation of the problem in this research is how to improve the ability to read beginning through serial image media for group A children at Kindergarten Bungong Nanggroe, Padang Tiji District, Pidie Regency? Padang Tiji District, Pidie Regency. This type of research is Classroom Action Research (PTK). The instrument used was an observation sheet, the number of samples was 12 children and the data were analyzed using a percentage formula. The results showed that in the description of the observation of children's activity in the first cycle, the total score obtained was 52% underdeveloped (6 children), 31% began to develop (3 children), developed according to expectations 14% (2 children), and developed categories Very good 2% (1 child). Whereas in the second cycle for the underdeveloped category 6% (1 child), 16.6% starting to develop (2 children), the developing category according to expectations was 37% (4 children) the very well developed category was 39.5% (5 children) ). Based on these data, it can be concluded that serial image media can improve children's early reading skills.
Secure Encrypted Word Proximity Retrieval Framework for Outsourced Relational Database Backed Applications

Significant chunks of critical and sensitive data are being outsourced to untrusted public environments delivering commercial services. This is gradually becoming a serious threat for data security. Especially in these environments, it is usually necessary to safeguard sensitive data across its complete lifecycle (rest, transit and most crucial during-use). Mostly, data during-use still remains unsecured and hence most vulnerable. The enterprise applications generally use search queries for data retrieval from databases. These must be executed directly on encrypted data itself so as to achieve complete confidentiality of data throughout life cycle. In this paper, we present a framework to perform search based on proximity upon encrypted data while most research efforts are limited to only search based on exact keyword. We propose a novel framework for proximity-based retrieval on encrypted data for applications which are supported by relational databases at back ends. This framework comprises of a trusted proxy to search application’s query over encrypted data hosted on outsourced database server while maintaining perfect secrecy by encryption algorithm involved. This is achieved by allocating words into domains, represented by their handles. The scheme presents two novelties. Firstly, the scheme supports security in all online transactional processing (OLTP) operations. This is evident in performance statistics observed. Secondly, it does not require any changes to existing stack of applications, thus it becomes practical toward real-world applications.
Sustainability in Banking Industry: A Study with Special Reference to Public Sector Banks in Chennai City

Banking Sustainability is a more composite word that concerns itself with, initiatives, processes and features that aid the banking sectors reach a level of sustainability in the forums of economy, environment and societal segments. It aims to perform banking practices and innovative initiatives using information technology and physical infrastructure efficiently and effectively with minimum impact on the environment. Technological development has played a vital role in the current business world. The advancement in the Technology has changed the entire process of banking practices. The research article intends to identify sustainability practices and its implementations in public sector banking industry. This empirical study is based on the data gathered from the people of Chennai who work in banks of public sectors.
CRITERIA-BASED ASSESSMENT AS A FACTOR OF INCREASING THE EFFECTIVENESS OF PEDAGOGICAL INTERACTION OF PARTICIPANTS IN THE EDUCATIONAL PROCESS OF THE UNIVERSITY

Improving the efficiency of the students' learning process, finding ways to activate their independence, the teacher and the student entering into a productive dialogue are topical issues of modern education. In the conditions of the credit system of teaching students, the main tasks are to unify the amount of knowledge, create conditions for maximum individualization of training, strengthen the role and effectiveness of independent work of students. We believe that students' mastery of self-control and mutual control skills through the use of criteria-based assessment technology is extremely necessary, and the use of criteria allows us to assess the advantages and disadvantages of specific assessment procedures. The article describes the results of a pedagogical study conducted by the authors among students of the 1-2 courses of the Innovative Eurasian University, where the method of L.V. Baiborodova was chosen as a tool to identify problems of interaction between a teacher and students. In the course of the study, the problems encountered by students in the learning process were analyzed, algorithms for organizing and conducting lectures and practical classes were proposed, allowing the teacher and the student to build an effective interaction process, the results of testing the proposed algorithms were described. The conducted experiment showed that the use of criteria-based assessment allows to effectively organize pedagogical interaction at the university.
Based on Internet + College English Teaching Model Innovation Research

Technological changes affect many fields such as healthcare and education. In the context of the Internet, many traditions are facing challenges. Only with the Internet+ thinking can better adapt to this change, and it is also a kind of thinking that must be possessed that will not be eliminated in the future. First of all, the breadth of thinking has been fundamentally expanded compared to the traditional. Second, the means to complete education and teaching are more abundant. Finally, the development and application of disciplines have been upgraded on the original basis, and students are also required to have more comprehensive capabilities. This is the influence of Internet+ on the education and teaching model, and this influence is no exception from basic education to higher education.
The Effect of Assessment On Motivation in a Virtual Reality Based Serious Game

A thesis report that investigates if there is a connection between the gamification attribute called Assessment and the learning outcome called Motivation. Furthermore, we investigate the existing ...
ABSA ANALYZER FOR EFFICIENT ASPECT EXTRACTION AND SUMMARIZATION

With the rapid growth in e-commerce websites, consumers are also interested in reading consumer reviews that share customer feelings about a product's different features before making buying decisions. Within this paper we present ABSA (Aspect-Based Sentiment Analyzer), based on customer feedback for the performance of aspect-level sentiment analysis. In the proposed approach, users will train models on the target domain for the output of aspect level sentiment analysis tasks in the first step. In the second step, a web application is made available from which an end-user may post comments to evaluate feelings at aspect level. In the third step tweets and reviews are produced which are important to the user defined keyword and which correspond to interesting aspects. The framework is developed using state-of-the-art approaches to aspect term extraction, aspect category detection and the detection of polarity aspects.