Reviewerly/exHarmony huggingface dataset:
Competence and safety of digital environment consumption by children and parents

Today we are witnessing the active introduction of information technologies in all spheres of life, which has led to an increase and reproduction of the digitalisation risks. This requires the state to form a society with high digital literacy. The authors studied digital literacy of students of grades 1-8 of secondary schools in Yakutsk and their parents within assessing digital literacy level of the population in Russian regions, assessed their knowledge of security bases in network space. The main method of collecting information was an online questionnaire. In the course of the study the competence levels in the ﬁeld of searching for information on the Internet through search engines, computer skills, the digital consumption indicators of children and parents, the social networks use, the goods and services consumption, the multimedia content production, etc., were deﬁned. The authors noted a low digital security level and an average digital competence level in indicated population category having a quite high digital consumption level. The study showed that there are large gaps in the knowledge of both children, adolescents, and parents. Thus, the digital competences development relevance among population was demonstrated.
Edukasi Penggunaan Sistem Informasi Permintaan Liputan Pada PT Cendrawasih Wiputra Mandiri

PT. Cendrawasih Wiputra Mandiri (CWM) having its address at Danau Maninjau Street, Rufei No. 19 Sorong City, is a cable TV and Channel company that has a lot of demand for coverage both in the Sorong City area and outside Sorong City. However, information about the process of requesting coverage is still not optimal, this causes many customers who often cancel the process of requesting coverage due to lack of information about the process of coverage. Therefore, PT. CWM needs to take advantage of the website for business development, especially in terms of information related to coverage request services. The use of the website must be maximized by PT. CWM, many employees of PT. CWM which has not been able to operate the website for coverage requests properly. For this reason, the Community Service (PkM) team needs to educate about the use of the website. Education is an important thing and really needs to be done because with education PT. CWM employees can work more optimally, especially in terms of operating a website for coverage requests. The education carried out by the PkM team had a huge impact, because apart from teaching how to operate a website, the PkM team also shared knowledge about how to solve problems related to using the website. The main purpose of this PkM activity is to share knowledge and care for others, especially to help PT. CWM to continue to innovate and survive during the pandemic
A Recommendation System for Cloud AI Services

Many learned inference engines have been released as cloud-based AI services. However, learned AI services are black boxes, and it is difficult for users to decide which service to choose. We propose a comparison service to infer the best AI service by learning their different output results as training data. Our model, “AI for selecting the best AI,” involves meta-learning; it learns the output of the cloud-based AI service as metadata. We compared and evaluated the accuracy and cost of two proposed models that recommend the best among several commercial AI services and an ensemble method. The results of our experiments to infer face attributes (i.e., age and gender) on a face image dataset crawled from Wikipedia showed that the accuracy of our system was higher than that of single face classification cloud-based AI service. Notably, results on inferring age and gender, where training data for each service showed a significant difference in the tendency for accuracy, had 6.2% higher accuracy compared to existing cloud-based AIs.
FEASIBILITY OF VIRTUAL REALITY AS A CLASSROOM TOOL

This study tested the use of an Augmented/Virtual Reality system (AVRS) as an enhancement tool to increase student engagement, retention and learning in a classroom setting.The study identified trends relating to the interest level of students when curriculum was delivered through a virtual environment.The study used a simulated solar system application of five to ten minutes in duration, which was shown to students from Upward Bound and Developmental English classes.The students were asked to evaluate the VR experience and the researchers noted their verbal responses.In the case of the developmental English class the students were asked to write an essay pertaining to their experience.The results were compiled and analyzed to identify trends that would either confirm or refute the idea of using an AVRS as an enhancement tool in educational settings.
Library Services in Improving Private Islamic Institutes Students' Reading Interest

This study aims to analyze library services at each private Islamic religious institute in Jambi Province. The focus of the discussion in this study is the implications of library services in increasing student interest in reading. The type of this research is the category of qualitative research with descriptive analytical study method. Data collection was carried out using observation, interview, and documentation techniques. Furthermore, the data were analyzed using reduction techniques, data presentation, and drawing conclusions. Finally, the data is declared valid/valid if it has gone through data triangulation. The results of this study indicate that the management of library services in increasing the reading interest of private IAI students in Jambi Province has not been carried out properly. Thus, it affects students' reading interest. This is due to several inhibiting factors, namely: library facilities that have not been maximized, operational costs are still minimal, managers or human resources are still low, low motivation from within the students themselves, and their busyness in activities outside campus.
Modelling repository of STEM projects as an open archive subsystem

The concepts of “repository” and “metadata” used in e-libraries and Internet resources are examined. The authors propose to make STEM projects repository a new form of projects preservation. The authors discuss repository hierarchical structure. They suggest to use two subject headings, i. e. student classification and tag clouds. Using these headings is characterized by specific character of STEM design. The examples of foreign repositories and their structure are provided, in particular SIEMENS repository and various formats of educational resources in such repositories. The authors introduce a new structure of data repository structured as a tag cloud comprising two areas – secondary school resources and academic resources. They point to the importance of resources of STEAM-STEM- projecting which is to support learning in natural sciences, to accumulate experiences of teachers, schoolchildren, professors and students in this area and to provide for prompt information retrieval and discovery of projects in various topics with interdisciplinary links and with the possibility of application in engineering disciplines.
User Manual for Addie-Based Model of Malay Language Learning Package

The National Education Policy upholds the Malay language (BM) by making it the official language and the language of instruction in schools and higher education institutions, including the Teacher Education Institution (IPG).Problems of using the Malay language exist among IPG students in particular the learning package used as teaching aids during the teaching practice in schools.To overcome these language errors, a user manual on the use of learning package is required.This study included two objectives: to identify the proficiency level of Malay language and develop a user manual on the use of BM learning packages based on the ADDIE Model.This method of preparing the user manual was guided by the ADDIE Model with five phases: Analysis, Design, Development, Implementation and Evaluation.The methodology employed was a qualitative method and involved 33 students majoring in the Malay language.The data were collected through analysis of language errors in learning packages and also questionnaires.The findings indicated that the students had committed 28 morphological errors.After the respondents used the user manual for the learning package, morphological errors indicated a decrease of 10 morphological errors.The improvement percentage for morphology was 64%.The Cohen Kappa index analysis for expert validation of the user manual was on a very good scale, K = 0.86, and the percentage of experts agreement was 93.3%.In conclusion, the user manual improves the understanding of the Malay grammar among the Teacher Education Institution students.
Dealing with COVID-19 in Sweden

In dealing with the COVID-19 pandemic, Sweden for several reasons stands out in a European context. In general, most but not all measures have been soft in character in the sense that they do not impose legal obligations, and Sweden did not impose a total lockdown. The main idea behind this policy was that measures needed to instil voluntary adherence instead of being legally enforced, in order to be sustainable. It is clear that the responsible Swedish administrative agency (Folkhälsomyndigheten) from the beginning adopted a long-term strategy, based on science and experiences from other pandemics. The main criticism of the Swedish approach can be summarised as the timing of measures taken (described by some as a lack of understanding of the initial urgency), the decentralised health care and crisis management system, and the lack of resources to test and conduct contact tracing in the initial phase of the pandemic. This chapter analyses and explains the Swedish approach from a constitutional law perspective.
The maximum cardinality of trifferent codes with lengths 5 and 6

A code $\mathcal{C} \subseteq \{0, 1, 2\}^n$ is said to be trifferent with length $n$ when for any three distinct elements of $\mathcal{C}$ there exists a coordinate in which they all differ. Defining $\mathcal{T}(n)$ as the maximum cardinality of trifferent codes with length $n$, $\mathcal{T}(n)$ is unknown for $n \ge 5$. In this note, we use an optimized search algorithm to show that $\mathcal{T}(5) = 10$ and $\mathcal{T}(6) = 13$.
Latent Space Virtual Adversarial Training for Supervised and Semi-Supervised Learning

Virtual Adversarial Training (VAT) has shown impressive results among recently developed regularization methods called consistency regularization. VAT utilizes adversarial samples, generated by injecting perturbation in the input space, for training and thereby enhances the generalization ability of a classifier. However, such adversarial samples can be generated only within a very small area around the input data point, which limits the adversarial effectiveness of such samples. To address this problem we propose LVAT (Latent space VAT), which injects perturbation in the latent space instead of the input space. LVAT can generate adversarial samples flexibly, resulting in more adverse effect and thus more effective regularization. The latent space is built by a generative model, and in this paper we examine two different type of models: variational auto-encoder and normalizing flow, specifically Glow. We evaluated the performance of our method in both supervised and semi-supervised learning scenarios for an image classification task using SVHN and CIFAR-10 datasets. In our evaluation, we found that our method outperforms VAT and other state-of-the-art methods.
L**: A First-order Polarity Logic with Plural Domains

An alternative formal language (L**) is constructed that better mirrors the structure of natural language (for example, by treating numerical expressions as predicates and thereby divorcing cardinality and quantification). It is shown how directional entailingness can be understood in terms of polarity, and how the properties of generalized quantifier theory can be cashed out within the formal structures of the new formal language.
Stratification of Breast Cancer in it's Preliminary Stages

Classifying breast cancer in its preliminary stages is done with the help of machine learning and the concept of Transfer Learning Algorithm. Here, the classification is done by labeling the tumor as benign or malignant. The machine learning algorithms are implemented by using the scikit library in which transfer learning is also available. The algorithm completely depends upon the dataset that&#x0027;s run through it and the accuracy of the same. To get the best result, the usage of a pre-trained model approach will bolster the rate of accuracy. Once the algorithm is run, the desired result would be the algorithm predicting if the tumor is benign or malignant so the patient can get the most optimal care.
Analyzing of Cyber-Security Concepts on Twitter

Today's buzzwords are cyber-security and social media.With the advancement of technology and the increased usage of the internet, these concepts are becoming more prominent and research on this subject is expanding.This paper addresses the issue of cyber-security and which professions in different business sectors discuss the topic of cyber-security on Twitter.Therefore, cyber-security concepts and contributors on Twitter are analyzed separately.In that way, business sectors that contributes to cyber-security are tried to be deduced with respect to different concepts.In addition, focuses of business sectors on cyber-security concepts are analyzed.The proposed paper demonstrates the application of the K-means clustering method to cyber-security concepts on Twitter and experts who posted tweets about these concepts.
Fake Media Products As Speech Aggression Provokers In Network Communication

The paper deals with the problem of the potential aggressive impact of fake media products on a user of a social net. The authors raise three important questions. Firstly, is network communication safe enough to users or does it need to be secured? Secondly, whether speech aggression in new media is invoked by fakes. And thirdly, how to prevent the harmful impact of faking and other aggressive behaviour of social net users. These questions are central to an understanding of how to deal with criminal speech interaction and countermeasure violent speech aggression that is virally invoked by fakes. The results of the undertaken speech-related research provide the insight into the phenomena of online abuse and the anti-aggression strategy based on special linguistic knowledge that can help to detect fake media narrative. The article also problematizes straightforward interconnection of fakes and violent speech aggression, as the impact of fake media products is not obligatory criminal but always, one way or another, harmful. Obviously, media fake product integrated with online abuse can cause aggressive reaction among online participants involved in the reference situation as well as among third parties offline. The authors focus on linguistic markers that can help to identify forgery in the presence of significant "artefacts" occurring in the production of a fake media product.
An Applied Mean Substitutions Technique for Detection of Anomalous Value in Data Mining

In the numerical value database, inliers in a database are subset of observations adequately small enough compared to the rest of the observations, which appears to be inconsistent with the remaining data set. They are the result of instant failures or early failures, experienced in many life-test experiments. The problem is how to handle Inliers in a dataset, and how to evaluate the Inliers. This paper describes a revolutionary of approach that uses Inliers detection as a pre-processing step to detect the Inliers and then applies Mean Substitution technique algorithm, hence to analyze the effects of the Inliers on the analysis of dataset.
Pengaruh Motivasi dan Intensitas Belajar di Rumah terhadap Prestasi Belajar Aqidah Akhlak

The purpose of this study was to determine: (1) learning motivation Aqidah Akhlak MI students Miftahul Ulum Tunahan 03 (2) Knowing the intensity of learning at home in the Aqeedah Akhlak subjects MI Miftahul Ulum Tunahan 03 students (3) learning achievement Aqidah Akhlak subjects MI Miftahul Ulum Tunahan 03 students (4) the influence of motivation and intensity of learning at home on learning achievement Aqidah Akhlak MI Miftahul Ulum Tunahan 03 students. Data collection techniques use: observation to collect learning motivation data, questionnaires for data on learning intensity at home and tests to collect learning achievement data Aqidah Akhlak. The population of MI Miftahul Ulum Tunahan students is 2018/2019 academic year, amounting to 104 people, because the population is widely sampled classically in class IV and V students, amounting to 25 people. Statistical analysis using multiple regression formulas. The results show that simultaneously there is a significant positive effect of learning motivation and intensity of learning at home on learning achievement Aqidah Akhlak MI Miftahul Ulum Tunahan 03 students. Based on statistical analysis with multiple regression formulas showed a significance level of 5% or 1%. Where the magnitude of Freg is 11.13 then compared with Ftable with df = 2: 22, for a significance level of 1% = 5.72 and for a significance level of 5% = 3.44. So Freg&gt; F table. Stelain was also found to be determined by 58%, which means that motivation and intensity of learning at home had a positive effect of approximately 58% on Aqidah Akhlak learning achievement.
LEARNERS' SPEAKING SKILLS WITH SPEECH DELAY BARRIERS IN PRIMARY SCHOOL

This study aims to describe the speaking skills of learners who have speech delay barriers in elementary school. Qualitative research methods of case studies. Child research subjects who had speech delaybarriers. Data collection techniques in the form of oral tests, observations, interviews, and documentation. Instruments in the form of oral tests with the form of story texts and instruments in the form of interview question guides and observation guides. Data analysis includes data reduction, data presentation, and conclusions. The results showed that learners with speech delay barriers had speech skills that were still less seen from the language and non-language aspects. This is due to individual factors of quiet speech delay learners and lack of confidence, family genetic factors that make learners experience speech delay,and environmental factors that makestudents' social interactions limited. Efforts applied in improving speech delay learners' speaking skills are using concrete learning media in the form of images, applying drill methods and question and answer methods, and providing motivation.
CET Resource Database Construction Model Based on Cloud Computing

Chinese students began learning English during compulsory education, have a long history of English learning, and focus on vocabulary, grammar, and other aspects of the language in middle school. Teaching resources include a variety of teaching conditions, such as materials. In a broad sense, they also include educational policies and other contents. They typically include teaching materials, cases, films and television, pictures, courseware, teacher resources, teaching aids, and infrastructure. In this case, cloud computing provides a good technical platform for solving the problems mentioned above in college English teaching (CET). Cloud computing enables the desktop use of Internet resources while reducing personal computer performance. In this paper, we will create a data resource data bank based on the cloud computing concept, making the most of existing resources, avoiding repeated development, and achieving curriculum content sharing. Reduce the cost of developing online courses, shorten the development cycle, and ensure that they are of high quality. This paper investigates the use of cloud computing to build a CET resource data bank. The cloud computing platform enables multiperson collaboration, document creation, editing, and sharing, all of which are characteristics of constructivism and collaborative learning theory.
A proof of P != NP (New symmetric encryption algorithm against any linear attacks and differential attacks)

a proof of p != np
Efficient bitrate ladder construction for live video streaming

In live streaming applications, service providers generally use a bitrate ladder with fixed bitrate-resolution pairs instead of optimizing it per title to avoid the additional latency caused to find optimum bitrate-resolution pairs for every video content. This paper introduces an online bitrate ladder construction scheme for live video streaming applications. In this scheme, each target bitrate's optimized resolution is determined from any pre-defined set of resolutions using Discrete Cosine Transform (DCT)-energy-based low-complexity spatial and temporal features for each video segment. Experimental results show that, on average, the proposed scheme yields significant bitrate savings while maintaining the same quality, compared to the HLS fixed bitrate ladder scheme without any noticeable additional latency in streaming.
Türkçe Metin Madenciliği için Dikkat Mekanizması Tabanlı Derin Öğrenme Mimarilerinin Değerlendirilmesi

In recent years, with the decrease in computational costs and the increase in data volume, significant achievements have been done in the field of deep neural network models for constructing effective learning models on big data.Deep neural network architectures have been successfully applied in many fields such as speech recognition, computer vision, as well as natural language processing problems such as sentiment analysis, text classification, and machine translation.In text classification problems, architectures such as recurrent neural networks, long-short-term memory architecture and gated recurrent unit are effectively used.Recurrent neural networks (RNN) are not efficient when learning long-term dependencies.In this architecture, tokens are processed sequentially, resulting in a state vector representing the data seen after each token.RNN-based architectures suffer from the problem that the state at the end of long sentences often does not contain information about early observed markers, due to the vanishing gradient problem.The attention mechanism makes it possible for a model to look directly at the state of an earlier point in the sentence and take advantage of it.Thus, all cases can be accessed and a more effective text modeling can be performed by providing clearer information about very distant related markers, according to some criteria of relevance learned with the current marker.The attention mechanism has been successfully applied in many natural language processing tasks, especially machine translation and text summarization.In this study, the performances of attention mechanism-based deep learning architectures for Turkish sentiment analysis are comparatively examined.In experimental analysis, recurrent neural network, long short-term memory architecture (LSTM), gated recurrent unit architecture (GRU), global attention mechanism-based LSTM, self-attention mechanism-based LSTM, hierarchical attention mechanism-based LSTM, global attention mechanism-based GRU, self-attention mechanism-based GRU and hierarchical attention mechanism-based GRU were evaluated.Attention mechanism-based architectures are observed to significantly increase the rate of correct classification for sentiment analysis.