Reviewerly/exHarmony huggingface dataset:
FEATURES OF THE FORMATION FUTURE PRIMARY SCHOOL TEACHER’S CRITICAL THINKING

The article investigated the features of the formation future primary school teacher’s critical thinking. Currently it was found the concept of forming critical thinking of the individual is recognized worldwide and implemented at all levels of education. Based on the study of a number of scientific papers, it is established that the analytical component of primary school teacher’s critical thinking is organically present at all stages of work with younger students, it allows to track positive and negative changes, as well as identify errors and inaccuracies in solving professional problems. It is noted that the development of critical thinking among students requires such an organization of educational work, which will be aimed at stimulating the understanding of the material and the formation of their own judgments and creation independent approaches to solving various scientific problems. Methods and techniques of formation future primary school teacher’s critical thinking are considered. It is noted the methodical ways and methods of forming critical thinking are working with different types of texts, visual methods and techniques of organizing information, asking questions, educational discussion, methods of reflection. The main methods and techniques for forming critical thinking of future primary school teachers are: cluster (“bunch”), “brainstorming”, Insert (interactive tag system for effective reading and thinking), mental map method, “written discussion”, project techniques . It is noted to form students’ skills of critical thinking – the task of all disciplines of the educational program of training future primary school teachers. It is determined that sufficient opportunities for the formation of critical thinking are seen in the inclusion in the educational process of such forms of independent work as compiling structural and logical schemes, annotations, writing and defending essays, reviewing essays by colleagues, scientific articles; creative works, creative reports, project activities, etc. It is established that there are many methods and techniques for forming critical thinking and depending on the specifics of the discipline being studied and the goals pursued by the teacher, it is possible to use certain types of these techniques, as well as their combination.
The Use of YouTube Videos in English Language Teaching: A Perspective of Indonesian Undergraduate Students Majoring in English Language Education

This study aims to investigate undergraduate students’ perspective toward the use of YouTube in online and face-to-face learning in which the videos used were made specifically by the lecturer for learning syntax. This study employed a descriptive quantitative method. The data were obtained by distributing survey-based questionnaires to 17 participants studying at a college majoring English Language Education. The results show that participants have strongly positive perspective toward the use of YouTube in both online and face-to-face learning. On their perspective, YouTube videos made are relevant to the course being studied; attractive for its convenience, affordability and accessibility; and effective to help them understand the lesson. It also motivates them to learn well and to participate in the class. So, it is better for lecturers to have a YouTube channel with their own learning videos to support their students in both face-to-face and online learning.
EXTYFD: Implementation of Expert System as A Diagnosis and Suggestion for Management of Tifoid Fever Using Borland Delphi to Improve Work Effectiveness

In the Medical field, expert systems can be used to diagnose diseases.EXTYFD is a program used to diagnose Typhoid fever.This program is intended to assist new doctors (health workers) in determining the type of disease, as well as helping us as the general public to find out the type of illness and suggestions for handling it, based on the symptoms or complaints felt by the patient.EXTYFD traces the rules using the Backward Chaining method and makes the program using Borland Delphi software.Broadly speaking, the EXTYFD program has been running well, among others, being able to diagnose typhoid fever and its comparative diagnoses and presenting suggestions for its treatment.The program also provides facilities to add to the knowledge database with a more user-friendly interface.Both adding patient data, as well as adding data for typhoid fever itself, such as symptoms, rules and suggestions for treatment.This EXTYFD program can display user identification, is also equipped with a password to maintain the security of data stored in the knowledge base, as well as a help menu to assist users in using the program.This program is expected to be a contribution to the advancement of the medical world.This expert system program can increase the effectiveness of the operational work of health services such as hospitals or clinics.Because it can provide time efficiency where patients do not have to wait long to get health services, energy efficiency: does not require a lot of energy to operate this system.Cost efficiency: no expensive hardware or server investment required, just install on existing PC.
Hate Speech or Xenophobia Law Violation

Information technology that is developing at this time will make it easier for people to know or communicate remotely in various parts of the earth instantly in seconds, though. The facilities can be used starting from radio, television, telephone, mobile phone, telegram, facsimile, and the internet
The Scientific Synergy in Handling the Crisis of The Covid-19 Outbreak: Privacy Protection Vs. Public Information Transparency

There are three interrelated things in scientific synergy in handling the Covid-19 response: government policies (both local and national), community attitudes, and no less important are, the role of technology.Since the initial instance was discovered, the spread of Covid-19 viral infections has risen.The debate around granting Covid-19 Positive Patients access to medical record data raises both positives and negatives in the community.If we are looking at the studies that has been published by researchers from other countries, this article intends to evaluate the viewpoints of numerous rules in assessing or examining medical record details, the shape of legal protection and the ramifications, and legal remedies for applied practice.According to the article, medical record data is a person's right that is both secret and limited.The legal protection afforded to a patient's medical record data is insufficient.Several nations have used patient personal data to predict the proliferation of the Covid-19 Virus, in accordance with the criteria of proportionality, need, and aim limitation.
Inner Fingerprint Check Criminal Action Investigation

This research is based on dactyloscopy at the crime scene and can be used as a clue for investigators in uncovering a criminal offense.This study aims to describe the function of dactyloscopy in the criminal investigation process and describe the dactyloscopy requirements to be evidence in the criminal investigation process.This type of research is normative law, and the approach method is normative juridical.The data technique collection is literature study and analysis of primary and secondary legal materials.This study indicates that fingerprints determine the perpetrators of crime, and fingerprints can be evidence of letters if proven by powder, brush, evaporation with sodium, and silver nitrate.
Money Laundering And Tax Evasion Resulting From Cyber Crimes Through Digital Currency (Crypto Currency)

Along with the rapid development of technology and the increasing prevalence of Cryptocurrency trading, it has raised concerns about the impact of the widespread use of new forms of digital money instruments (Crypto Currency).This study aims to examine the crime of money laundering and tax evasion originating im cyber crime through Crypto Currency.The problems discussed in this study are: 1.What are the legal rules governing the role of the profession as a reporting party in preventing and eradicating criminal acts of money laundering and tax evasion from the proceeds of cyber crimes through Crypto Currency?2. How is law enforcement carried out by the court as one of the sub-criminal justice systems for its role in preventing and eradicating money laundering and tax irregularities?This research is analytical prescriptive, with a multi-entry or multidisciplinary approach, which uses data obtained from library research and field research.The data collection tools used are document studies and interviews.The research phase is literature, which is supported by interviews.The data obtained were analyzed qualitatively with normative juridical and empirical juridical approaches.From the results of the study it can be concluded that: 1.The law has an important role to regulate the role of the Profession as a Whistleblower to prevent and eradicate criminal acts of money laundering and tax evasion.The role of the profession is a reflection of the embodiment of professionalism in the legal field, so as to realize the interests of humanity and society, it is regulated in State Government Regulation Number 43 of 2015 concerning Reporting Parties in the Prevention and Eradication of the Crime of Money Laundering.2.Law enforcement carried out by the courts against perpetrators of money laundering crimes that run more concentrated on corporate crimes, and law enforcement against perpetrators of tax evasion crimes experiencing obstacles or obstacles are the legal substance (norms), legal structure (law enforcement), legal culture and procedural law (formal law) rather than orientation to the return of assets resulting from crime.
HealthBlock: A Modular Framework for a Collaborative Sharing of Electronic Health Records Based on Blockchain

Abstract Electronic Health Records (EHRs) play an important role in our life. However, most of the time, they are scattered and saved on different databases belonging to distinct institutions (hospitals, laboratories, clinics, etc.) geographically distributed across one or many countries. Due to this decentralization and the heterogeneity of the different involved systems, the medical staff are facing difficulties in correctly collaborating by sharing, protecting, and tracking their patient’s electronic health-record history to provide them the best cares. Also, patients have no control on their private EHRs. Blockchain has many promising futures useful for the healthcare domain because it provides a better solution for sharing data while preserving the integrity, the interoperability, the availability, and even the privacy than classical client-server architectures used to manage EHRS. This paper proposes a modular framework called HealthBlock for a collaborative sharing EHRs and their privacy-preserving with a granular access control. Different technologies have been combined to access this goal. the InterPlanetary File System (IPFS) technology stores and shares patients’ EHRs in distributed Off-Chain storage and ensures the record’s immutability; the Hyper-ledger Indy gives patients full control over their EHRs and the Hyper-ledger Fabric store the patient access control policy and delegations.
Research on the Controllability of a Class of Nonlinear Intelligent Systems based on Fractional Order Analysis

This paper discusses the controllability of a class of nonlinear intelligent systems. Using fractal and fractional functional analysis methods, under certain conditions, the controllability, stability and Stabilization problem, under the condition of multi-parameter synergy, the conditions for blasting and bifurcation in large time state is given. With the help of the relevant theory of fractional calculus and the Mittag-Leffler function, a relatively simple and practical M-matrix form is early enough. Under this constraint, the Mittag-Leffler stability and asymptotic stability of this kind of system are achieved. For the time period problem of two types of high-order nonlinear artificial intelligence systems, the existence, uniqueness and weak controllability of their controllability is proved.
Enhancing student learning with domotics projects

The aim is to bring students closer to domotics by creating prototypes of products for everyday use, which will allow them to improve the quality of life in their homes. For this purpose, a two-level analysis is generated: 1) construction and operation and 2) data storage and analysis. It is intended that students compare the four projects, exchange parts between the devices, face the challenges of their construction, reflect on the operation of the components and analyze the data collected. The objective is to provide a fundamental approach to the implementation of domotics, and, in the future, they will be able to build their projects.
Coherent conversion between one and two photons in waveguides with engineered dispersion

High-efficiency photon-pair production is a long-sought-after goal for many optical quantum technologies, and coherent photon conversion processes are promising candidates for achieving this. We show theoretically how to control coherent conversion between a narrow-band pump photon and broadband photon pairs in nonlinear optical waveguides by tailoring frequency dispersion for broadband quantum frequency mixing.
Computational Processes for General Intelligence

&lt;p&gt;The ‘brain-mind-intelligence’ structure may be considered analogous to a ‘computer-operating system (OS)-application’ construct. Software development would be far more difficult without the benefit of abstractions like file and memory handles, and graphical user interfaces, implemented in operating systems. The easy access to application-level semantics, provided by the infrastructure of the OS, simplifies application development. Abstractions can play a similar role in producing intelligent systems. The power of abstractions may be determined by their ability to unify the treatment of several types of higher concepts. Unifying various concepts in the domain of intelligence, such as problems, solutions, objects, and emotions, through abstractions will be of immense value. This paper shows how ‘higher-level perceptions’ could be used to serve this objective and construct an OS-like infrastructure. With the infrastructure in place, ordinary software objects developed and deployed using standard methods, become accessible using the semantics provided by the infrastructure. Now, after brief training exercises, the objects would be available for intelligent use. The focus, therefore, is on the design of the infrastructure that could play a mind-like role in humans. &lt;/p&gt; &lt;p&gt;The resulting model is then evaluated in terms of features against criteria set forth independently, by Newell, Sun, Vernon, and others. In addition, a new measure of intelligence introduced in this paper is used to compare the proposed modeling method with some of the major methods developed over the years.&lt;/p&gt; &lt;p&gt;&lt;br&gt;&lt;/p&gt;
Image Captioning Using Deep Learning Model

Image Captioning means that the natural language descriptions are generated automatically based on the content of an image. It's an important aspect of scene comprehension since it integrates computer vision and natural language processing knowledge. Numerous methods and algorithms are developed by researchers to increase the accuracy of image captioning. However, it is one of the major questions for future researchers to get optimized result in captioning an image. Furthermore, there are thousands of gray-scale images that are captioned. In this proposed work, different pre-trained models are used to extract features of images through Convolutional Neural Network (CNN) for colored images and gray-scale images from dataset and then, the extracted features are fed into LSTM, which generates caption for images. At last, the model’s accuracy of color and gray-scale images are studied to determine the model’s capability in captioning both types of images.
The nexus of blockchain and governance: A use case of blockchain on trade finance

Having both opportunities and threats, blockchain is a game-changer disruptive innovation in our time. It keeps penetrating a wide scope of areas including banking, insurance, supply chain, trade finance, agriculture, etc. We explore this multifaceted technology as the first building block of our study. As a second building block, we focus on the governance concept and then we analyze the nexus of blockchain and governance. Our study contributes to the extant scarce literature by covering the recent developments on the subject. Following Liu, Lu, Yu, Paik, and Zhu (2022) we conduct our study through several steps. The literature review of our study is based on Web of Science and Google Scholar academic databases. Studies are selected according to the predefined inclusion and exclusion criteria. The review period of the study is the last five years. According to our analysis, we detect a literature gap between on-chain and off-chain governance. We believe our study contributes to filling this gap. We propose a recipe to the argument of Kaufman, Heister, and Yuthas (2021) that suggest blockchain technology has failed to produce promised benefits for enterprise networks despite its potential. Considering the increasing importance of trade finance especially during and afterward the COVID-19 pandemic, we bring forward our solution by employing a real use case of trade finance. During this effort, we explore XinFin and XinFin Digital Contract (XDC) as an example that can create added value from micro and macroeconomic perspectives simultaneously. Our future research will base on blockchain governance practices in specific sectors.
Transfer learning data adaptation using conflation of low-level textural features

Adapting the target dataset for a pre-trained model is still challenging. These adaptation problems result from a lack of adequate transfer of traits from the source dataset; this often leads to poor model performance resulting in trial and error in selecting the best performing pre-trained model. This paper introduces the conflation of source domain low-level textural features extracted using the first layer of the pretrained model. The extracted features are compared to the conflated low-level features of the target dataset to select a higher quality target dataset for improved pre-trained model performance and adaptation. From comparing the various probability distance metrics, Kullback-Leibler is adopted to compare the samples from both domains. We experiment on three publicly available datasets and two ImageNet pre-trained models used in past studies for results comparisons. This proposed approach method yields two categories of the target samples with those with lower Kullback-Leibler values giving better accuracy, precision and recall. The samples with the lower Kullback-Leibler values give a higher margin accuracy rate of 6.21% to 7.27%, thereby leading to better model adaptation for target transfer learning datasets and tasks
Tele-education and adaptive behavior with autism spectrum disorder, in children from 1 to 5 years old

This research aims to determine the relationship between tele-education and adaptive behavior in autism spectrum disorder in children aged 1 to 5 years. To do this, a cross-sectional, descriptive and correlative non-experimental design study was carried out, the study population consisted of 120 people, and the sample was of a non-probabilistic census type. For data collection, a tele-education survey and an adaptive behavior survey were produced, both with high levels of reliability. Statistical treatment included connection tables, bar graph, analysis and interpretation. For validation, we used Spearman's confirmation coefficient, Rs=0.730, which shows a high positive confirmation with p=0.003. Therefore, it is concluded that in the National Institute of Rehabilitation-Chorrillos there is a significant relationship between tele-education and adaptive behavior in children from 1 to 5 years old.
Re-Label By Data Pattern Is All You Need For Knowledge Driven Deep Learning

&lt;p&gt;In industry deep learning application, we should fix the badcase after we achieve more than 95% accuracy at dev dataset. The badcase reason is from the wrong rule/knowledge of human labeling and will cause low accuracy under human evaluation. In this paper, we propose the pattern-based method to fix the badcase for industry application inference. We propose the pipeline to solve the problem and improve the accuracy of human evaluation. The experiment results verify our idea.&lt;/p&gt;
Animatronika – bábművészet és technológia

Through the topic titled Animatronics – Puppetry and Technology, I propose to examine mechatronic devices and robotised puppets, which are used more and more often not only in the arts and entertainment world, but also in medical technology, for treatment and therapeutic purposes. I seek answers to two questions, one, what new horizons are opened up with the integration of mechatronic devices into artistic creation, two, what are the potential advantages of scientists building on puppetry techniques and the thousands of years of practical experience inherent in them, during the development of mobile and companion robots.
Assessing the readability of social studies textbooks for the Junior High schools in Ghana

This study was designed to assess the readability level of Ghana Education Service (GES) approved Social Studies textbooks that are currently in use in Junior High Schools (JHS) in Ghana. The sample of the study consisted of the GES approved Social Studies textbooks for JHS 1-3 currently in use. Thirty different texts (ten from each textbook) were randomly selected for the readability test. The instrument used for data collection was textbook readability test. The data were analysed using free online readability test. The results of the findings showed that the GES approved Social Studies textbooks were difficult, compared to their grade level. The study recommended that Social Studies textbooks should be assessed to see their readability level before they are given to students. This is necessary because readable textbooks motivate students to read and learn better.
IMPLEMENTATION OF GAMIFICATION ELEMENTS IN ONLINE LEARNING USING LMS MOODLE

This article discusses means of gamification elements, used in order to achieve higher learners, satisfaction level in the online studying process. Moodle is represented as an exemplary system, due to its widespread usage in educational institutions. First, premises of desirable learner; behavior is set up, and the second means of creating a dynamic environment for both students and teachers, mostly for receiving quick feedback and therefore boosting motivation. Moodle plug-ins for gamifying the environment are laid out along with proposed factors for analysis of their influence.
A Concept Map based Teaching of Compiler Design for Undergraduate Students

In undergraduate engineering, most of the subjects do not have the open visibility of the Industry and Research requirements. Students are interested mostly on subjects which are useful for Industry placement. They do not show interest in non-open visibility subjects if an instructor teaches by simply following the textbook. Considering this, we presented a concept map based teaching methodology with Research and Industry assignments and problems. The proposed methodology focus on improving the teaching quality and students’ understanding level. In this paper, we have taken the Compiler Design subject and presented the concept map. To understand the eectiveness of the proposed methodology, the students feedback was collected and evaluated using the sign-test and the students’ submitted problems and assignments were evaluated to understand their level. The analysis results show that most of students studied Compiler Design with interest as a result of proposed teaching methodology.