Reviewerly/exHarmony huggingface dataset:
Methods, Principles and Means of Implementation of Blended Learning of Future Teachers-Philologists in Higher Education Institutions

The article is devoted to one of the actual problems of blended learning in higher education. In particular, it is noted that the problem of principles, methods, and the means of implementation of blended learning of teachers-philologists in higher education is currently in demand and requires immediate solution.&#x0D; The definition of the term "blended learning" is revealed, given that in the pedagogical literature there is no consensus and this concept is considered as a model, approach, technology, form, mixture of methods and strategies, program, it is defined that blended learning is a process of obtaining knowledge, skills and abilities, accompanied by a combination of different learning technologies using ICT (information and communication technologies).&#x0D; It was specified what informational and methodological support was provided to higher education institutions in the organization of blended learning at the state level of the Ministry of Education and Science.&#x0D; The main attitude in the work focuses on the didactic principles of blended learning in higher education (humanities, stimulation and motivation, consciousness, activity and independence, individual approach, strength of knowledge acquisition, clarity, system and consistency, flexibility, interactivity, accessibility, integrity of learning, adaptability, mobility, compliance with learning technologies, openness of the process of education) and reveals their essence.&#x0D; Were considered and specified the methods of blended learning (traditional and computer methods) of future teachers of philology in higher education institutions. Was generalized the means of realization of blended learning.&#x0D; It was found that the required platforms and services for the organization of blended learning in the training of future teachers of philology in higher pedagogical institutions were: Classroom, Zoom, Meet, Moodle, Uran, Teams, etc.&#x0D; It was mentioned about the necessity to create a feedback platform in the organization of blended learning.
Mesa Python platform for agent-based modelling

Mesa is a licensed by Apache development environment for agent-based models (or ABM) in Python. It allows users to create agent-based models using built-in basic components (such as spatial and agent schedulers) or custom implementations; visualize them using the interface in a web browser; and analyze their results using Python data analysis tools. The purpose of the development of the environment was the desire of the authors to create an alternative for NetLogo, Repast or MASON based on the Python language.
VE-VMI: High-Performance Virtual Machine Introspection Based on Virtualization Exception

Virtual machine introspection (VMI) mostly relies on memory virtualization mechanisms to enforce access restrictions on certain areas of the virtual machine (VM)’s physical memory, including the page tables managed by the guest OS. Consequently, the CPU will generate exceptions on any in-VM memory access not complying with the restrictions imposed by the VMI, switching from the VM to the hypervisor (HV) (in a so-called “VM-exit”), giving the VMI module the possibility to analyze the faulty memory access and take the needed decision to protect the VM. Such a protection strategy could suffer significant performance penalties, as a large number of VM-exits could be generated, though most of them being irrelevant to VMI, like changes of accessed or dirty bits made by the hardware page-table walker. We propose an approach to consistently reduce the number of irrelevant memory-related VM-exits: by using the Intel virtualization exception (#VE) extension, the faulty memory accesses can be handled directly inside the VM, filtering out the ones irrelevant for the VMI, while calling the HV (i.e. generate VM-exits) only for the remaining ones. The in-guest filtering agent is protected against attacks from a compromised VM, by isolating it inside a separate guest physical address space, different by and inaccessible from the one used by the VM while running its own code. We implemented our #VE-based solution in the Xen hypervisor, obtaining performance improvements between 30% and 80% for the applications protected by our VE-VMI module.
Sentiment analysis on myindihome user reviews using support vector machine and naïve bayes classifier method

In the era of globalization, the internet has become a human need in doing various things. Many internet users are an opportunity for internet service providers, PT Telekomunikasi Indonesia (Telkom). One of PT Telkom's products is IndiHome. As the only state-owned enterprise engaged in telecommunications, PT Telkom is expected to meet the needs of the Indonesian people. However, based on the rating obtained by IndiHome products through the myIndiHome application on Google Play, it is 3.5 out of 87,000 more reviews. The reviews focus on how important the effect of word-of-mouth is on choosing and using internet provider products. The review data was collected on November 1, 2020 to December 15, 2020, with a total of 2,539 reviews as a sample. The sentiment analysis process that has been carried out shows that the number of reviews included in the negative sentiment class was 1.160 reviews, and the positive class was 1.374 reviews out of a total of 2,539 reviews. The results indicate that service errors in IndiHome services are still quite high, reaching 46.7% as indicated by the number of negative reviews. The classification results show that the average value of the total accuracy of the Support Vector Machine (SVM) method is 86.54% greater than Naïve Bayes Classifier (NBC) method which has an average total accuracy of 84.69%. Based on fishbone diagram analysis, there are 12nd problems on negative reviews that classify problems 5P factors: Price, People, Process, Place, and Product.
Fast Bounded Suboptimal Probabilistic Planning with Clear Preferences on Missing Information

In the real-world, robots must often plan despite the environment being partially known. This frequently necessitates planning under uncertainty over missing information about the environment. Unfortunately, the computational expense of such planning often precludes its scalability to real-world problems. The Probabilistic Planning with Clear Preferences (PPCP) framework focuses on a specific subset of such planning problems wherein there exist clear preferences over the actual values of missing information (Likhachev and Stenz 2009). PPCP exploits the existence and knowledge of these preferences to perform provably optimal planning via a series of deterministic A*-like searches over particular instantiations of the environment. Such decomposition leads to much better scalability with respect to both the size of a problem and the amount of missing information in it. The run-time of PPCP however is a function of the number of searches it has to run until convergence. In this paper, we make a key observation that the number of searches PPCP has to run can be dramatically decreased if each search computes a plan that minimizes the amount of missing information it relies upon. To that end, we introduce Fast-PPCP, a novel planning algorithm that computes a provably bounded suboptimal policy using significantly lesser number of searches than that required to find an optimal policy. We present Fast-PPCP with its theoretical analysis, compare with common alternative approaches to planning under uncertainty over missing information, and experimentally show that Fast-PPCP provides substantial gain in runtime over other approaches while incurring little loss in solution quality.
The use of comic book as a media in teaching reading comprehension to improve students' vocabulary mastery

Improving vocabulary mastery of students requires creativity in finding some strategies in order that students are motivated to memorize the vocabulary. This research aimed to use a comic book to improve student's vocabulary mastery through reading comprehension. The researcher focused on the use of Snow White comic book in improving students’ vocabulary mastery. The data were collected by doing tests. The tests were divided into pre-test and post-test to see the students’ ability on their vocabulary mastery before and after the treatment, and a questionnaire was used to see the students’ responses toward the approach. The samples are the students of MAN 2 Montasik Aceh Besar, consisted of 40 students who were divided into experimental class and control class. The obtained data were analyzed using descriptive statistics through SPSS Version 22. The result of the hypothesis testing of this research showed that students’ vocabulary mastery was significantly improved. The students’ responses toward the use of comic book to improve their vocabulary mastery were positive and the students showed their interest in reading. Therefore, the use of comic book to improve student's vocabulary mastery through reading comprehension is suggested to be used by teachers to help students in learning and memorizing vocabulary.
The Problem Of Text Cohision In Computer-Mediated Communication

The entire set of message chains that form the blog text is presented in the form of certain rhetorical relationships, in which each message is an agreement / disagreement with the interlocutor's opinion, an affirmative statement or a denial.In the blog text rhetorical structure, the microtheme being discussed is represented in terms of combinations of affirmation and negation in stimulating and reacting messages (for example, negation -affirmation; negation -negation -negation, etc.).Such combinations embody the nature of the relationship of agreement and disagreement of the interlocutors with each other's opinions.In order to detail the pragmatic and cross-cultural specifics of rhetorical cause-and-effect relationships between different components of the blog text, we analyze individual statements as the basic units of the blog text.These statements are segmented into separate syntactic syntagmas, which are characterized by some propositional content.The blogger and respondent's dialogical moves often form a complete statement, the coherence of which is provided by one or another subordinate conjunction, introductory word or adverb.Rhetorical cause-and-effect relationships ensure the coherence of the blog text by: 1) modus-dictum and modus-modus coordination of the components of the corresponding syntactic construction; 2) structural and semantic coherence of the text generated jointly by the blogger and respondents; 3) programming the topic of computer-mediated communication, which is based on detailing the facts covered in the blog text and discussed by the interlocutors; 4) expanding the basic frame of communication, which was set in the incentive message, due to private slots that enter additional information.
Spontaneous Exploratory Choices Under the Probabilistic Gambling Task Involve the State of conflict: A Pupillometric Study

This paper describes the process of capturing an expert’s knowledge in the form of human understandable rules and then inserting them into a self-organizing map neural network. The Dynamic Cell Structure (DCS) is a form of self-organizing map used for many purposes, including classification and prediction. The DCS is a topology-preserving network that starts with no pre-structure, but assumes a structure once trained. This paper explores applying the DCS to analyse a social science data set that contains some of the many factors that may influence the mortality rate of a region.
Perancangan Sistem Informasi Peminjaman dan Pengembalian Rekam Medis Rawat Jalan di Rumah Sakit Muhammadiyah Bandung

This research was conducted based on the problem of managing the borrowing and returning outpatient medical records at the Muhammadiyah Hospital Bandung which aims to find solutions to these problems to support the effectiveness of medical record services. The research method used in this research is a qualitative method with a descriptive approach. The data collection techniques used were interviews, observation, and study approach. In making the software design the writer uses the waterfall method and the supporting applications used are Microsoft Visual Studio 2010 and Microsoft Access 2013. From the results of the research conducted, the authors found several problems in the management of borrowing and returning outpatient medical records, namely: (1). There were no medical records found on the storage shelf; (2). Recording of borrowing and returning medical records still uses a manual system; (3). The absence of reports on borrowing and returning medical records. The suggestions that can be given by the author, namely : (1). It is better if the borrowing of medical records is determined by the due date so that there are no more medical records that are late to be returned to the storage room; (2). An information system is needed on borrowing and returning medical records to support activities in the hospital, especially in making reports on borrowing and returning medical records. The result of this research is an information system for borrowing and returning medical record files at Muhammadiyah Hospital Bandung.
A Newly Proposed Prospective and Robust Computer Networking Model Architecture Based on the Infrastructure of Cloud Computing Contrivance

Abstract: Computer Networking Play’s a major role for data communication or data sharing and data transmissions from one location to another, which are geographically differ, but in today’s scenario where the main and primary major concerns are not to data transfer but also utilize all resources with greater efficiency and also preserves the confidentiality and integrity of the messages with respect to speed and time with lower Bandwidth and also consume a very low computational costs with low power supply and redirect to optimality. Cloud Computing also play’s a significant role to access data at geographically different locations. So In this paper we create a fusion of Computer Networking Architecture and Cloud Computing Architecture and released a very much superior fundamentally strong Cloud computing based Computer Networking model, which works on the concepts of ‘Virtualization’. Because when the number of hardware components (Servers) drastically increases all factors which are responsible to make possible networking among nodes are also consume each resources at extreme level, and networking becomes complex and slow, that’s why we used the concept of Virtual Machine. In this paper we proposed a Computer Networking model using the concepts of Cloud Computing. This model also suitable for data transmission but also take concern the most significant feature of Computer Networking, which is Data Security. This model also used some Proxy servers/ firewalls to take concern some security mechanisms. In this paper we also proposed Communication Oriented model among the Intercluster domains that how one node which belongs to another CLOUD cluster make possible communication among other InterCLOUD clusters with respect to data security measures. In this paper we proposed three models related to this networking model, which is CLOUD Networking Infrastructure, Connection Oriented model, Communication Oriented model. The detailed description of all three models are in the upcoming sections of this paper. Keywords: Cloud computing based computer networking model, A virtual model for computer networking, Computer Networking model based on virtualization, Virtualization based computer networking model.
Development of an Optimised Dataset for Training a Deep Neural Network

Artificial intelligence in computer vision has focused on improving test performance using techniques and architectures related to deep neural networks. However, improvements can also be achieved by carefully selecting the training dataset images. Environmental factors, such as light intensity, affect the image’s appearance and by choosing optimal factor levels the neural network’s performance can improve. However, little research into processes which help identify optimal levels is available. This research presents a case study which uses a process for developing an optimised dataset for training an object detection neural network. Images are gathered under controlled conditions using multiple factors to construct various training datasets. Each dataset is used to train the same neural network and the test performance compared to identify the optimal factors. The opportunity to use synthetic images is introduced, which has many advantages including creating images when real-world images are unavailable, and more easily controlled factors.
Analisis Implementasi Aplikasi Pembelajaran Interaktif Calistung Dengan Pendekatan Technology Acceptance Model

The advancement of smartphone technology has an impact in the field of education, especially in application-based interactive learning media. Based on the results of interviews at the Paya Laba Public Elementary School (SDN), some of the students have difficulty in using interactive learning media based on applications, ranging from operating skills, equipment, habits, benefits and others. Thus, to measure the level of acceptance of the use of interactive learning applications for reading, writing and arithmetic skills at SDN Paya Laba culd conducted by using a theoretical method which described the level of technology acceptance, namely the Technology Acceptance Model (TAM). However, the study aims to analyze the implementation of interactive learning reading, writing, arithmetic based on android applications. The test was run by measuring the influence between variables in the TAM model, which labelling as Perceived Ease of Use, Perceived Usefulness, and Attitude towards Using Technology, Behavioral Intention to Use and Actual Technology Use. The data in this study were obtained from questionnaires which filled out by the respondents. The data analyzed with Structural Equation Modeling approach based on Partial Least Square (PLS-SEM) by using the SmartPLS application. The stages of data analysis started from designing the structural model, designing the measurement model, evaluating the measurement model, evaluating the structural model, and testing the hypothesis. From the research results based on the seven proposed hypotheses, there are six hypotheses declared accepted and one hypothesis rejected.
SSH Vocabulary Initiative - What users want

SSHOC will build the Social Sciences and Humanities part of the European Open Science Cloud.One of the SSHOC project's core objectives is to foster the transition from the current Social Sciences and Humanities (SSH) landscape to a cloud-based infrastructure that will operate according to the FAIR principles, offering access to research data and related services adapted to the needs of the SSH community.Furthermore, the tools, services, repositories and other resources developed and enhanced in SSHOC will be featured in the SSH Open Marketplace.The SSH European Research Infrastructure Consortia (ERICs) partnering in SSHOC are exploring and enabling collaboration and deeper integration of each other's infrastructures.One topic that is of relevance for all SSHOC SSH stakeholders is that of managing and using vocabularies.Here we use vocabularies as a general term covering a range of semantic artefacts such as wordlists, taxonomies and thesauri.The SSH vocabularies are essential for a proper description of resources and phenomena and in SSHOC many tasks are concerned with them.In SSHOC, the SSH Vocabulary Initiative was launched to coordinate related vocabulary activities and investigate, inform and exchange expertise on vocabularies and the platforms that are hosting and managing them.
Використання проєктних технологій у формуванні підприємницької компетентності майбутніх web-дизайнерів

International scientific and practical conference «Pedagogy, psychology and teaching methods: international experience» : conference proceedings, July 16–17, 2021. Riga, Latvia : «Baltija Publishing», 2021. 295 pages.
A Survey on Unsupervised K-Means Algorithm in Big Data Environment

Due to the rapid development in information technology, Big Data has become one of its prominent feature that had a great impact on other technologies dealing with data such as machine learning technologies. K-mean is one of the most important machine learning algorithms. The algorithm was first developed as a clustering technology dealing with relational databases. However, the advent of Big Data has highly effected its performance. Therefore, many researchers have proposed several approaches to improve K-mean accuracy in Big Data environment. In this paper, we introduce a literature review about different technologies proposed for k-mean algorithm development in Big Data. We demonstrate a comparison between them according to several criteria, including the proposed algorithm, the database used, Big Data tools, and k-mean applications. This paper helps researchers to see the most important challenges and trends of the k-mean algorithm in the Big Data environment.
SISTEM INFORMASI PELAYANAN SIM

The driving license administration service system is a special service provided by Nasional Police to people who want to make a SIM. This service system can be done online. The current application has made it a lot easier in the process of making up the SIM card production. However, there are some problems related to internal reports that must be reported because the service is not yet available in an existing application, so some recapitulation processes are still done conventionally and technical constraints on the server network. This study aims to create a service management information system application (SIMPEL SIM) that can provide solutions to internal reporting and server network technical constraints. The method used software development is waterflow. This application handles the printing of bank payment receipts automatically, granting the applicant's registration number automatically, printing the SIM application form on the form provided. Verification of the completeness of the file, validation of the score of the theory test, practice 1 and practice 2, validation of sim issuance and printing of temporary sim numbers if there is a technical problem in the existing network server. The use of the SIMPEL SIM application makes it easy to recapitulate internal reporting and can improve public services.
Sign and Search: Sign Search Functionality for Sign Language Lexica

Sign language lexica are a useful resource for researchers and people learning sign languages. Current implementations allow a user to search a sign either by its gloss or by selecting its primary features such as handshape and location. This study focuses on exploring a reverse search functionality where a user can sign a query sign in front of a webcam and retrieve a set of matching signs. By extracting different body joints combinations (upper body, dominant hand’s arm and wrist) using the pose estimation framework OpenPose, we compare four techniques (PCA, UMAP, DTW and Euclidean distance) as distance metrics between 20 query signs, each performed by eight participants on a 1200 sign lexicon. The results show that UMAP and DTW can predict a matching sign with an 80% and 71% accuracy respectively at the top-20 retrieved signs using the movement of the dominant hand arm. Using DTW and adding more sign instances from other participants in the lexicon, the accuracy can be raised to 90% at the top-10 ranking. Our results suggest that our methodology can be used with no training in any sign language lexicon regardless of its size.
Research on Open Teaching of Engineering Survey Laboratory Course of New Engineering Course

This paper expounds the reform methods and ideas of open teaching of engineering surveying experimental course, the specific measures of building open surveying laboratory, and the teaching effects obtained in cultivating students' innovative spirit and ability and realizing resource sharing.