Reviewerly/exHarmony huggingface dataset:
Grammar System of TCFL Driven by Neural Network Technology

With the economy’s continued and stable growth, China’s political and economic influence in the international community has grown, and more and more friends from all over the world are requesting to learn Chinese and visit China. The growth of information technology and curriculum integration has had a significant impact on TCFL (teaching Chinese as a foreign language). Facing the new situation will enable us to gain a fresh perspective on the current state of TCFL grammar system research. Through specific teaching practice, this paper verifies the effectiveness of teaching Chinese as a foreign language and cultural vocabulary. This paper proposes a grammar error correction scheme based on hybrid models—Transformer model and N-gram model—that dynamically combine the outputs of different neural modules to improve the model’s ability to capture semantic information, with the goal of correcting Chinese grammar errors. Experiments show that the Transformer and N-gram model-based Chinese grammar error correction strategy performs well in the global effect, and the overall performance is the best in the detection and positioning levels. At the detection level, the model in this document has the highest error correction accuracy of 0.64 and the highest recall rate of 0.67. The results show that adding an attention mechanism to a grammatical error correction model can improve its computational efficiency.
IMPROVING STUDENT LEARNING OUTCOMES THROUGH THE USE OF ANDROID-BASED MEDIA AND LEARNING MOTIVATION

This study aims to determine 1) The positive relationship between the use of android-based media and the learning outcomes of Indonesian students at grade XI 2) The positive relationship between learning motivation and learning outcomes for students at grade XI 3) the Positive relationship between the use of android-based media and learning motivation together -the same as the results of learning Indonesian students at grade XI. This study uses a survey method. The sampling technique used a random sampling technique so that the sample size was 100 respondents. The collection of data on learning outcomes uses document data and learning motivation using an instrument in the form of a questionnaire. Then the data analysis technique used analysis regresi. The results showed. There is a positive relationship between the use of android-based media and the learning outcomes of students at grade XI 2) There is a positive relationship between learning motivation and learning outcomes of students at grade XI 3) There is a positive relationship between the use of Android-based media and learning motivation -the same as the Indonesian learning outcomes students at grade XI.
Design and Implementation of a Final Project Plagiarism Detection System Using Cosine Similarity Method

Plagiarism is an act of taking ideas, taking research results, acquiring research results, and summarizing writing without mentioning the source, either intentionally or unintentionally. The cosine similarity method can be used to calculate the score of similarities between documents by comparing existing documents on the database with uploaded ones to gain a similarity percentage. External plagiarism detection (EPD) is used to compare the contents of articles. The design and implementation of the system will be carried out in several stages in the hope that the system can work optimally and detect text similarities accurately. This research objective is to check the plagiarism rate of the document using the cosine similarity method as a method of calculating word equations called Kipcheck. The purpose of checking the level of plagiarism is to ensure that the documents created have a minimum level of fraud to avoid academic sanctions. Kipcheck uses three application system tests; maximum word calculation that can be processed; comparing application and manual calculation; and testing the consistency of application calculation results based on two different schemes.
A text mining and topic modeling based bibliometric exploration of information science research

This study investigates the evolution of information science research based on bibliometric analysis and semantic mining. The study discusses the value and application of metadata tagging and topic modeling. Forty-two thousand seven hundred thirty-eight articles were extracted from Clarivate Analytic's Web of Science Core Collection 2010-2020. This study was divided into two phases. Firstly, bibliometric analyzes were performed with VOSviewer. Secondly, the topic identification and evolution trends of information science research were conducted through the topic modeling approach latent dirichlet allocation (LDA) is often used to extract themes from a corpus, and the topic model was a representation of a collection of documents that is simplified using topic-modeling-toolkit (TMT). The top 10 core topics (tags) were information research design, information health-based, model data public, study information studies, analysis effect implications, knowledge support web, data research, social research study, study media information, and research impact time for the studied period. Not only does topic modeling assist in identifying popular topics or related areas within a researcher's area, but it may be used to discover emerging topics or areas of study throughout time.
Penyisihan Logam Fe Pada Air Gambut Menggunakan Membran Chitosan Sebagai Adsorben

Peat water in terms of quality cannot be used as a source of clean water or drinking water, so it needs to be processed. One alternative treatment that can be used is the adsorption process with a column system using a chitosan membrane (the content of amine groups contained in the chitosan membrane has a good ability to absorb metals). This study aims to remove Fe metal in peat water. Variations carried out were Fe concentrations of 2, 3 and 4 mg/L and flow rates of 2, 3, 4 and 5 mL/minute. The results obtained are the best Fe metal removal efficiency of 92.20% with a final concentration of 0.312 mg/L at an Fe concentration of 4 mg/L and a flow rate of 2 mL/minute. The results of the study have met the quality standards set by the Minister of Health of the Republic of Indonesia Number 32 of 2017 concerning Sanitary Hygiene
Comparison of Signature Forgery Detection Architectures

Abstract: In today's society, we use signatures for many important documents like passports, driving licenses, bank cheques, etc. But signatures can be forged in multiple ways, which can create a number of problems, such as identity theft, hacking, fake identification, etc. To reduce these problems, our project is about developing a system for detecting whether a signature is forged or real from a dataset of signatures. For our project, we are developing an offline signature verification system. This system is based on CNN (Convolutional Neural Network) and SNN (Siamese Neural Network). In this project, we will be comparing both CNN’s and SNN's to find which produces a better result. We are implementing the project using a custom CNN, a CNN with VGG16 architecture, a custom SNN and a SNN using the SigNet architecture.
Implementation of Think Pair Share during Limited Face-to-Face Learning to Improve Students’ activeness, Concept Understanding, and Learning Outcome

Activeness and concept understanding during limited face-to-face learning needs to be studied. This study is reviewed from the activeness, concept understanding, and student learning outcome through the Think Pair Share learning model with several actions. Classroom action research with a qualitative approach was carried out on a public junior high school at Pasuruan, Indonesia with 16 grade 8 students as research subject. The instruments of this research were test, observation sheet, and documentation. Data analysis was carried out by describing the activeness, concept understanding, and student learning outcome. The results show that there was a significant increase in the activeness and concept understanding so that student learning outcome also increase by using Think Pair Share during limited face-to-face learning.
Comparing the accuracy of ANN and ANFIS models for predicting the thermal data

The study aims to propose a suitable prediction model to deliver the full heating season's thermal performance dataset by using short-term measured data during the system operation period.Two machine learning-based models, BackPropagation Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System are compared by utilizing the measured data of indoor temperature and relative humidity.The independent variables of the prediction are obtained from the weather data, in addition to the building energy simulation model.Conversely, the data of the dependent variable are obtained from the real measurements from inside of the building for 31,5 days of the heating season, starting from February 22 nd , which is called the first heating season.Moreover, the entire heating season of the building is evaluated between November 15 th and March 21 st , which is called the second heating season when the building's monthly consumption exceeds 14 kW/m 2 .The first prediction approach is the feed-forward Artificial Neural Network (ANN) with Back Propagation Learning System (BPS).Four ANN models are structured by input-output and one hidden layer is performed.The second prediction approach is the Adaptive Neuro-Fuzzy Inference System (ANFIS).The Sugeno ANFIS method is utilized in this prediction work.Eight ANFIS models are structured by 6 layers are performed to achieve the prediction.Besides, the main motivation for approaching ANFIS is to avoid the stochasticity of the measured temperature and humidity data.The prediction results are compared with the measured data of the second heating season.The comparison showed that the ANFIS model is more efficient since it achieved an 85% accuracy rate for the indoor temperature and 81% for the humidity prediction.While the ANN prediction accuracy is 81%, 80% relatively for the temperature and humidity.Then the comparison is scaled by selecting the most ordinary period in the measured data to be the data sample that will be used in the comparison.The second comparison showed that the ANFIS model is once again better than the ANN model since the ANFIS prediction accuracy becomes 88% for temperature and 90% for humidity, while the ANN prediction accuracy becomes 83% for temperature and 87% for humidity.Nevertheless, the stochasticity of the measured affected the prediction results in accuracy rates.Hence, according to the achieved accuracy rates, both the ANFIS and ANN approaches are highly validated in this type of prediction.
Implementation of digital competencies in higher education educational programs in Russia

In the context of digitalisation, the transformation of the educational process is inevitable and is a priority issue for any country that wants to maintain or improve its position on the world stage. The article presents a comparative analysis of digital competencies and the possibility of their implementation in the higher education system in Russia. The comparison of the formulated competencies in the methodology approved by the Order of the Ministry of Economic Development of the Russian Federation No. 41 dated January 24, 2020, as well as the International Telecommunication Union and other European organisations is considered. The descriptors (knowledge, skills and abilities) of graduates in various fields who, in the era of digitalisation, must have the necessary digital competencies are identified. Today, professional standards, even in the humanities, define the requirements for technical and computer skills. The article proposes formulations of universal competencies in the higher education system based on the analysis.
Model Media Interaktif Articulate Storyline Untuk Menumbuhkan Kemandirian Membaca Permulaan Peserta Didik SD

Obstacles that occur when teaching early reading in low grades are the lack of media used to help students learn to read and the lack of human resources in the use of technological devices, especially in the current pandemic era. This study aims to develop an Android-based interactive learning media for beginning reading with the help of Articulate Storyline software and determine the feasibility of the learning media. The method used is the Research &amp; Development (R&amp;D) method. The data collection technique was done through a questionnaire, the research instrument used a questionnaire sheet. This study resulted in Android-based applications and products assessed from the feasibility of using media as measured by the quality of content and objectives and instructional quality. Assessors are conducted by peers, on the assessment of the quality of content and objectives, the assessor states that the learning media is in the appropriate category, and based on the instructional quality assessment questionnaire on the trial, the learning media is also declared to be in the appropriate category so that the learning media can be used to assist the learning process.
Digital Dialogue in Learning: Cognitive, Social, Existential Features and Risks

Digitalization of socio-cultural phenomena, including the education system, generates transformations of their qualitative characteristics and parameters, which requires research from the standpoint of methodological analysis and assessment of their possible consequences on humans and society. A significant element of the digital environment, in general, and educational, in particular, is the dialogue, the role of which has both cognitive and ideological, existential, social aspects. The purpose of the research is a philosophical analysis of the digital transformation of dialogue in the context of the educational process, an assessment of its potential and impact on the individual. The research methodology has a complex, interdisciplinary character and is associated with the application of an existential approach to understanding the essence of dialogue (M. Bakhtin, M. Buber, G. Marcel, E. Levinas), the theory of the development of individual thinking by L.S. Vygotsky, developed by the author of the theories of electronic (digital) culture and based on modern developments in the field of the introduction of digital tools in education. The study shows that dialogue in the digital learning environment becomes not so much a form of rapprochement, integration of subjects, as a form of autonomy, isolation, individuals, which changes the nature of learning and has social and existential consequences. This creates the need to transform the digital learning environment when using it from the position of supplementing it with ethical, socio-psychological and emotional components and support tools for the student. Based on the existential-axiological analysis, the positive and risky features of digital dialogue as one of the phenomena of electronic culture and online learning tools are revealed. The concept of digital dialogue in learning, the characteristics of its features, functions, role and influence on the learner in the digital environment are presented. The difficulties of dialogic learning characteristic of the digital environment are revealed, recommendations of a methodological and methodical nature for application in the education system are presented.
Ensuring the Data Integrity in Infocommunication Systems

The article is devoted to the study of the perspectives of steganography to ensure integrity. The definition of information integrity is presented, which meets the new requirements and the definition of cybersecurity. Integrity is achieved through the control and recovery of information. The article provides a detailed analysis of existing approaches to the construction of modern steganometric systems. The greatest attention in the article was paid to the method of hiding information in graphic containers. The proposed method is a modification of the well-known method of replacing the least significant bits. The main difference from the known method is that not all least significant bits are changed. The selection of the bits to be changed is carried out using a pseudo-random sequence generator, while, thanks to the proposed algorithm, no more than 3.12 percent of the bits are changed, which is the limit of visibility for the steganalyst. There are 6.25 percent of information bits in such a message.
A Research on the Establishment of a System Improving Teaching Ability of English Teachers in the Classroom Setting by Utilizing Artificial Intelligence

The efficient implementation of the artificial intelligence approaches could nobly resolve the deficiencies of the conventional approaches. This manuscript puts forward a scheme to construct a system that helps provide feedback on the teaching performance of English teachers in a classroom setting by utilizing artificial intelligence. Thus, the artificial intelligence-based framework is combined with the traditional system theories dealing with the teaching performance of English teachers in a classroom setting. For this purpose, the BP neural network is utilized to compute the teaching performance, which can effectively improve the teaching style in the classroom setting by updating the implemented teaching methodology, avoiding examination-oriented assessment, and increasing the multiorientation. To assure the rationality and effectiveness of the constructed scheme for English teachers, a simulation experiment is conducted. So, the teaching evaluation system of the English teachers is analyzed based on the constructed scheme. The experiment suggests that traditional system theories when combined with artificial intelligence schemes under the proposed scheme are found to be more suitable for modern English teaching activities in the classroom setting.
Privacy-preserving multi-factor authentication and role-based access control scheme for the E-healthcare system

E-healthcare assists medical specialists in remotely collecting patient health data and providing remote health diagnoses. The roles are distributed among the system's users, contrasted between admin to data entry within certain rules and policies. Role-based access control (RBAC) is a technique of advanced access control that restricts key operations of users (addition, deletion and modification) access based on a user's role within a healthcare system. This paper proposes a privacy-preserving using RBAC and smart multi-factor authentication for the healthcare system to overcome the limitation flaw in previous schemes such as security risk tolerance, scalability and dynamism. This work relies on low-complexity cryptographic hash functions and symmetric operations to authenticate users while using an asymmetric cryptosystem based on the Schnorr digital signature lightweight operation to authenticate the administrator to provide multi-factor authentication. The administrator represents the system's core, and any his information leak could attack the entire system and its components. The proposed scheme conducted two thorough formal security proofs for the proposed work based on informal analysis and the Scyther tool. Furthermore, comparisons with other schemes reveal that the proposed scheme provides greater security features, and resisting attacks than the others while also being efficient in computing and communication costs.
Urgensi Pengenalan Konsep Literasi Numerasi pada Anak Usia Dini

This study discusses the urgency of introducing the concept of numeracy literacy in early childhood. Numerical literacy is one of the most needed skills in facing the 21st century, especially for the young generation. The question still remains, when should these skills be introduced and trained to the young generation candidates. Should it be introduced and taught from an early age? The purpose of this study was to determine the urgency of introducing the concept of numeracy literacy in early childhood. This study uses a literature review method where the authors collect 7 studies related to numeracy literacy in early childhood. From the results of the review that the author conducted on the seven related articles, there are 3 (three) important reasons why numeracy literacy should be introduced to early childhood. Based on these reasons, the authors conclude that the urgency of introducing the concept of literacy to early childhood is quite high, because numeracy literacy is a basic skill that must be possessed in the 21st century and early childhood is a golden age where the level of intellectual maturity of children is formed up to 80%.
Application of Information Technology in the Inheritance and Communication of Tai Chi Culture in the Era of Big Data

With the advent of the era of big data, the development of Internet technology has provided more platforms for the development of traditional culture and expanded the scope of influence of traditional culture. In the development process of Tai Chi, how to give full play to the advantages of information technology, enhance the influence of Tai Chi, and promote the dissemination and inheritance of the Chinese traditional sports culture are the problems that need to be solved at present. This paper took the population of Tai Chi practicing in X community as the investigation object and analyzed the current inheritance and development status of Tai Chi, found out the main problems in the inheritance and development of Tai Chi, and finally put forward the path of using VR technology in information technology for spread. In addition, the satisfaction of residents with the transmission and inheritance of Tai Chi was measured at the policy, economic, social, and technical levels and compared with the satisfaction of residents before and after the application of VR technology through experiments. The results showed that after the use of VR technology, residents were more involved in Tai Chi and had better satisfaction at all levels.
GERNERMED++: Transfer Learning in German Medical NLP

We present a statistical model for German medical natural language processing trained for named entity recognition (NER) as an open, publicly available model. The work serves as a refined successor to our first GERNERMED model which is substantially outperformed by our work. We demonstrate the effectiveness of combining multiple techniques in order to achieve strong results in entity recognition performance by the means of transfer-learning on pretrained deep language models (LM), word-alignment and neural machine translation. Due to the sparse situation on open, public medical entity recognition models for German texts, this work offers benefits to the German research community on medical NLP as a baseline model. Since our model is based on public English data, its weights are provided without legal restrictions on usage and distribution. The sample code and the statistical model is available at: https://github.com/frankkramer-lab/GERNERMED-pp