Reviewerly/exHarmony huggingface dataset:
Financial literacy in Turkish preschool education

Financial literacy is one of the basic skills of the 21st-century. It is an important skill to survive in the complex economies of the modern era. It is better to develop financial literacy skills at early ages. This study aims to examine the current state of FL education in preschool education in Turkey. For this aim, in this qualitative study, the Turkish preschool education curriculum was examined and the interviews were conducted with 20 preschool teachers constituting the study group. The data collected from document analysis were subjected to descriptive analysis and the data collected by interviews were subjected to content analysis. Results of the study show that Turkish preschool education is not supportive of financial literacy both in terms of curriculum and the teachers. For a strong foundation of FL in Turkey, the Turkish preschool education curriculum should be revised and the preschool teachers must be supported in terms of the development of FL skills at early childhood.
ELECTRONIC PORTFOLIO AS A TOOL OF REFLECTING THE RESULTS OF SCIENTIFIC AND PEDAGOGICAL ACTIVITIES OF TEACHERS OF HIGHER EDUCATION INSTITUTIONS

In the period of digital transformation of all spheres of life, including the educational and scientific sphere, the opportunity for scientific and pedagogical workers (SPW) to present their achievements on the Internet, including the results of scientific and pedagogical activities becomes important. The results of scientific and pedagogical activities of SPW are not only certificates of various activities (training, internships, participation in various activities), but also profiles in scientific and metric databases and the number of citations of relevant publications, information about achievements, list of publications, information about the teacher (education, scientific degree, academic title), range of interests, victories of students under the guidance of SPW, etc. That is why the purpose of the article is to consider the possibility of using the electronic portfolio as a means of reflecting the results of scientific and pedagogical activities of teachers of free economic zones. The following research methods were used in this study: analysis, generalization, systematization. These methods were used to analyze and summarize the existing experience on this issue, as well as to systematize existing approaches to creating an e-portfolio. Under the e-portfolio of the scientific and pedagogical worker, we will understand the information system, which will contain all the information about the achievements of the scientific and pedagogical worker, including scientific work, awards, etc. The components that the electronic portfolio should contain are singled out if it is considered as a means of reflecting the results of scientific and pedagogical activities of teachers of free economic education. According to the authors, such a portfolio should contain: general information about the SPW: surname, name, patronymic, academic degree, academic title, information about higher education (about all, if more than one), place of work, position, etc.; information on SPW achievements: awards, prizes, participation in events, victories in competitions, etc.; SPW profiles in scientific-metric databases: Scopus, Web of Science (Publons), DBLP, Index Copernicus, Google Scholar, etc., publications; certificates; additional useful links; contacts; abbreviated profile in English, information on inventions, patents, participation in international projects, intellectual property rights to the work. The electronic portfolio of the scientific and pedagogical worker plays the role of a means of reflecting the results of the scientific and pedagogical activity, and acts as a business card of the teacher. The availability of such a portfolio will ensure the availability of SPW data in open access on the Internet. Prospects for further research include the search for other means of reflecting the results of scientific and pedagogical activities, as well as their expert evaluation.
Kratt: Developing an Automatic Subject Indexing Tool for the National Library of Estonia

Manual subject indexing in libraries is a time-consuming and costly process and the quality of the assigned subjects is affected by the cataloger’s knowledge on the specific topics contained in the book. Trying to solve these issues, we exploited the opportunities arising from artificial intelligence to develop Kratt: a prototype of an automatic subject indexing tool. Kratt is able to subject index a book independent of its extent and genre with a set of keywords present in the Estonian Subject Thesaurus. It takes Kratt approximately one minute to subject index a book, outperforming humans 10–15 times. Although the resulting keywords were not considered satisfactory by the catalogers, the ratings of a small sample of regular library users showed more promise. We also argue that the results can be enhanced by including a bigger corpus for training the model and applying more careful preprocessing techniques.
Factors Impacting Users’ Compliance with Information Security Policies: An Empirical Study

One of the main concerns for organizations in today's connected world is to find out how employees follow the information security policy (ISP), as the internal employee has been identified as the weakest link in all breaches of the security policies.Several studies have examined ISP compliance from a dissuasive perspective; however, the results were mixed.This empirical study analyses the impact of organisational security factors and individual non-compliance on users' intentions toward information security policies.A research model and hypotheses have been developed in this quantitative study.Data from 352 participants was collected through a questionnaire, which then validated the measurement model.The findings revealed that while security system anxiety and non-compliant peer behaviours negatively impact users' compliance intentions, work impediments positively influence these intentions.Security visibility negatively influences users' non-compliance, and security education systems positively impact work impediments.This research will help information security managers address the problem of information security compliance because it provides them with an understanding of one of the many factors underlying employee compliance behaviors.
Dynamic Event-Triggered Predictive Control for Interval Type-2 Fuzzy Systems with Imperfect Premise Matching

This paper investigates the dynamic event-triggered predictive control problem of interval type-2 (IT2) fuzzy systems with imperfect premise matching. First, an IT2 fuzzy systems model is proposed, including a dynamic event-triggered mechanism, which can save limited network resources by reducing the number of data packets transmitted, and a predictive controller, which can predict the state of the system between the two successful transmitted instants to deal with unreliable communication networks. Then, according to the Lyapunov stability theory and imperfect premise matching method, sufficient conditions for system stabilization and the controller gain are obtained. Finally, the validity of the proposed method is demonstrated by the numerical examples.
Text Summarization in Multi Document Using Genetic Algorithm

Automatic text summarization is a representation of a document that contains the essence or main focus of the document. Text summarization is automatically performed using the extraction method. The extraction method summarizes by copying the text that is considered the most important or most informative from the source text into a summary [1]. Documents can be divided into two types, namely single documents and multi documents. Multi document is input that comes from many documents from one or more sources that have more than one main idea.This study aims to summarize the text using a Genetic Algorithm by paying attention to the extraction of text features on each chromosome. The feature extraction used is sentence position, positive keywords, negative keywords, similarity between sentences, sentences containing entity words, sentences containing numbers, sentence length, connections between sentences, the number of connections between sentences. The number of chromosomes used is half of the number of public complaints. The data used is data on public complaints against the DIY government from February 2018 to July 2020. The data is obtained from the e-lapor DIY website. From the test results, the average value of Precision 1, Recall is 0.71, and f-measure value is 0.79.
Entropy Query by Bagging-Based Active Learning Approach in the Extreme Learning Machine Framework for Hyperspectral Image Classification

Active learning (AL) technique is the classification of remote sensing images, where collecting efficient training data is costly in terms of labour and the time taken.The prime objective of AL technique is to obtain high classification accuracy with the training sample as compact as possible.Most studies on the classification of remote sensing images using AL, focused only on accuracy, with hardly any study on computation time.Keeping reduction of computation time as the objective, here we present, an entropy query by bagging (EQB)-based AL approach in the extreme learning machine (ELM) framework for remote sensing image classification.The performance of this approach is compared with the widely used support vector machine (SVM) AL framework in combination with different query strategies.To verify the efficacy of the study, the approaches were tested on two hyperspectral remote-sensing images, i.e.Kennedy Space Centre (KSC) and Botswana (BOT).The proposed system depicts competitive classification performance while significantly reducing computation time.
ROLE OF METASUBJECT EDUCATIONAL RESULTS IN LEARNERS’ PROFESSIONAL SELF-CONSCIOUSNESS FORMATION

The article reveals the notion of metasubject educational results that are closely connected with the formation of universal skills necessary for a specialist in demand in the contemporary society.&#x0D; The purpose of the article is to identify the influence of metasubject results on the learners’ mastering of knowledge, abilities and skills as well as to establish the relationship between formed competences and learners’ professional self-consciousness development.&#x0D; Materials and methods are considered to be theoretical research of discussed notions, analyses of literature, generalization and systematization.&#x0D; Results. Metasubject results are considered to be cross-cutting educational results related to universal competences formation in accordance with educational programs of basic general education and complete secondary education.&#x0D; The emphasis is placed on the development of cognitive, informative, communicative and regulatory competences while the latter is viewed as indicator of direction of learners’ professional self-consciousness formation. The article touches upon the role of the teacher in the formation of competences and metasubject educational results necessary for learners’ professional self-consciousness growth.&#x0D; Conclusions. The educational process should be organized in such a way to develop skills and abilities of learners using the most effective motivating means. The development of competences is to promote metasubject results necessary for learners’ professional self-consciousness formation and growth.
Recent Advances in Deep Reinforcement Learning Applications for Solving Partially Observable Markov Decision Processes (POMDP) Problems Part 2—Applications in Transportation, Industries, Communications and Networking and More Topics

The two-part series of papers provides a survey on recent advances in Deep Reinforcement Learning (DRL) for solving partially observable Markov decision processes (POMDP) problems. Reinforcement Learning (RL) is an approach to simulate the human’s natural learning process, whose key is to let the agent learn by interacting with the stochastic environment. The fact that the agent has limited access to the information of the environment enables AI to be applied efficiently in most fields that require self-learning. It’s essential to have an organized investigation—we can make good comparisons and choose the best structures or algorithms when applying DRL in various applications. The first part of the overview introduces Markov Decision Processes (MDP) problems and Reinforcement Learning and applications of DRL for solving POMDP problems in games, robotics, and natural language processing. In part two, we continue to introduce applications in transportation, industries, communications and networking, etc. and discuss the limitations of DRL.
When is BERT Multilingual? Isolating Crucial Ingredients for Cross-lingual Transfer

While recent work on multilingual language models has demonstrated their capacity for cross-lingual zero-shot transfer, there is a lack of consensus in the community as to what shared properties between languages enable transfer on downstream tasks.Analyses involving pairs of natural languages are often inconclusive and contradictory since languages simultaneously differ in many linguistic aspects.In this paper, we perform a large-scale empirical study to isolate the effects of various linguistic properties by measuring zeroshot transfer between four diverse natural languages and their counterparts constructed by modifying aspects such as the script, word order, and syntax.Among other things, our experiments show that the absence of sub-word overlap significantly affects zero-shot transfer when languages differ in their word order, and there is a strong correlation between transfer performance and word embedding alignment between languages (e.g., ρ s = 0.94 on the task of NLI).Our results call for focus in multilingual models on explicitly improving word embedding alignment between languages rather than relying on its implicit emergence. 1
A Survey on Sentiment Analysis Approaches in e-Commerce

Sentiment analysis represents the process of judging customers' behavior expression and feeling as either positive, negative or neutral.Hence, a tangle of different approaches for sentiment analysis is being used, reflecting analysis of unstructured customers' reviews dataset to guide and generate insightful and helpful information.The aim of this paper is to highlight research design of sentiment analysis and choice of methodological by other researchers in E-Commerce customers' reviews to guide future development.This paper presents a study of sentiment analysis approaches, process challenges and trends to give researchers a review and survey in existing literature.Next, this study will discuss on feature extraction and classification method of sentiment analysis of customers' reviews to have an exhaustive view of their methods.The knowledge on challenges of sentiment analysis underpins to clarify future directions.
Prediction of congestive heart failure in patients using artificial intelligence: proof of concept

Abstract Introduction Due to the aging of the population we are confronting ourselves with an increased number of patients with chronic heart failure which stands a prevalence of over 37,7 million cases worldwide, being a major public health issue, first by the substantial morbidity and mortality that carries and second by the economic burden it brings annually upon the health-care system. The main purpose of this study is to test a machine learning algorithm which can predict, through voice analysis the acutisation of heart failure, considering the particularities of the patient's voice. Methods The data we have used has been collected from a total of 16 patients, 9 men and 7 women, ages between 65 and 91 years old, who have agreed to take part in the study. The selective criteria of inclusion has been the cause of hospitalization, selecting only the patients presented with cardiogenic acute pulmonary edema, regardless the precipitation cause or other known cardiovascular comorbidities. With the same electronic device we have recorded each patient's voice, twice a day, starting from the day one of hospitalization, when their general status was critical, until the day of discharge, when they were clinically stable. Each voice recording containing specific keywords has been associated to the most used classification system for heart failure, the New York Heart Association Functional Classification and introduced into the machine learning algorithm. Results After integrating the information from 15 patients, the algorithm has classified correctly the 16th patient into the third NYHA stage, based only on his voice recording. Conclusion Voice is a cheap and easy way to monitor a patient's health status. The algorithm we have used for analyzing the voice provides high accuracy results, but for a larger dataset it might not be the best choice as it is computationally expensive. We are looking to obtain larger datasets and to compute more complex voice analyzer algorithms. Funding Acknowledgement Type of funding sources: None.
Evaluation and Speciation of Heavy Metals Contamination of Selected Artisanal Mining Sites in Mangu Local Government Area of Plateau State, Nigeria

Artisanal (illegal) mining has been reported to have environmental and health effects on the surrounding communities due to heavy metals pollution. The determination of total heavy metal concentration does not reflect the toxicity and bioavailability of the metals. Toxicity and bioavailability of the metals can be achieved by determining the form in which the metal exist in the environment (speciation). This present work evaluated the heavy metals’ {cadmium (Cd), copper (Cu), manganese (Mn), lead (Pb), zinc (Zn) &amp;nickel (Ni)} contamination and the form in which they exist at some mining sites in Mangu LGC, Plateau state, Nigeria. Aqua regia ((HCl + HNO3, 3:1 v/v) was used for total metal concentration while sequential extraction method was used to orderly determine the speciation of the heavy metals. The level of the heavy metals in the digested solutions were determined using Buck Scientific model 210VGP Atomic Absorption Spectrophotometer (AAS). The results divulged that the concentrations of the heavy metals were within the FEPA and WHO recommended permissible limit except Cd and Ni. The values of the metals at Mangu Halle mining site followed the sequence: Mn &gt; Zn &gt; Ni &gt; Pb &gt; Cu &gt; Cd whereas the sequence at Alogwom was Mn &gt; Zn &gt; Pb &gt; Ni &gt; Cu &gt; Cd. The results of the speciation indicated that all metals were bound to the five fractions with the residual fraction dominating except Cd which was bound mostly to the soluble and exchangeable fractions. It could be concluded that the presence of these heavy metals in the mobile fractions, indicate that they could be easily released to the environment from soil. Thus, they are also likely to cause toxicity in the environment. Proper monitoring of the mining activities in the communities was recommended.
Code switching found in cinta laura’s video on her instagram tv

This study concerns with the code switching found in Cinta Laura's video on her Instagram TV. Descriptive qualitative method is used for analyzing the data from ten videos. This study used the theory proposed by Poplack (1980) about types of code switching and the theory from Hoffman (1991) about the reasons of code switching. This study shows that there are three types of code switching found and six reasons of code switching found. The result of this study shows that intra-sentential switching is the most frequently used in types of code switching and particular topic is the most frequently used in the reasons of code switching. The phenomenon of code switching occurs in many media such as social media. By doing code switching, it is easier to build a sense of solidarity rather than using only one language. Therefore, code switching is an interesting topic to discuss in sociolinguistics research.
Constructing a software requirements specification and design for electronic IT news magazine system

Requirements engineering process intends to obtain software services and constraints. This process is essential to meet the customer's needs and expectations. This process includes three main activities in general. These are detecting requirements by interacting with software stakeholders, transferring these requirements into a standard document, and examining that the requirements really define the software that the client needs. Functional requirements are services that the software should deliver to the end-user. In addition, functional requirements describe how the software should respond to specific inputs, and how the software should behave in certain circumstances. This paper aims to develop a software requirements specification document of the electronic IT news magazine system. The electronic magazine provides users to post and view up-to-date IT news. Still, there is a lack in the literature of comprehensive studies about the construction of the electronic magazine software specification and design in conformance with the contemporary software development processes. Moreover, there is a need for a suitable research framework to support the requirements engineering process. The novelty of this paper is the construction of software specification and design of the electronic magazine by following the Al-Msie'deen research framework. All the documents of software requirements specification and design have been constructed to conform to the agile usage-centered design technique and the proposed research framework. A requirements specification and design are suggested and followed for the construction of the electronic magazine software. This study proved that involving users extensively in the process of software requirements specification and design will lead to the creation of dependable and acceptable software systems.
A lightweight magnetic gripper for an aerial delivery vehicle: design and applications

&lt;p&gt;In recent years, drones have become widely used in many fields. Their vertical flight capability makes these systems suitable for carrying out a variety of tasks. In this paper, the delivery service they provide is analysed. The delivery of goods quickly and to remote areas is a relevant application scenario; however, the systems proposed in the literature use electromagnets, which affect the duration of the flight. In addition, these devices are heavy and suffer from high energy consumption, which reduces the maximum transportable payload. This study proposes a new lightweight magnetic plate composed of permanent magnets, capable of collecting and positioning any object as long as it has a ferromagnetic surface on the top. This plate was developed for the Mohamed Bin Zayed International Robotics Challenge 2020, an international robotics competition for multi-robot systems. Challenge two of this competition required a drone capable of picking up different types of bricks and assembling them to build a wall according to an assigned pattern. The bricks were of different colours and sizes, with weights ranging from 1 to 2 kg. In light of this, it was concluded that weight was the most relevant specification to consider in drone design.&lt;/p&gt;