Reviewerly/exHarmony huggingface dataset:
Supplemental Material for Cognitive and Cultural Models in Psychological Science: A Tutorial on Modeling Free-List Data as a Dependent Variable in Bayesian Regression

In Supplementary Section A, we implement an alternative likelihood to the zero-one inflated beta, namely the ordered beta distribution.For technical details and background, see Kubinec ( 2022) and for practical implementation, see the R package ordbetareg (https: //github.com/saudiwin/ordbetareg)and source code for the present supplementary document.In Supplementary Section B, we illustrate and implement alternative likelihood models that do not require transforming free-list data to salience scores, as discussed briefly in the main manuscript.We integrate key code chunks in the text but refer to the source code for full reproducible code.For simplicity, we restrict the examples to the Model 1 data and exclude field-site specific 'random effects' in all models.In Supplementary Section C, we first present plots for Models 3-8 (Figures 10 and11).Then, we present results for the reduced models, where only non-zero free-list responses are retained .Finally, we present results from leave-one-group-out crossvalidation (Table 3), an alternative model comparison to the approximate leave-one-out cross-validation as presented in the main manuscript.
NETOCRACY AS A FORM OF INFORMATION SOCIETY MANAGEMENT

The article examines the change in the paradigm of modern societyʼs existence, the transformational processes of which affect all its spheres. Special attention is paid to the study of mutual relations and communication between various social institutions, in particular, in the field of public administration. Attention is focused on non-democratic processes in modern management activities as a special form of information society management. The development of modern management is considered through the prism of deliberative democracy, in which members of society recognize each otherʼs ability to deliberate (public exchange of reasonable judgments).
Phase refractive index measurement of thick glass plates with a spectrally resolved interferometer

Measurements of phase refractive indexes of thick objects by using fitting method have been reported in many papers, but the fitting method produces errors in the fitted coefficients of a fitting function. In this paper it is made clear that the thickness of object, for which the phase refractive index can be measured exactly, is limited by the errors. Phase refractive indexes of three kinds of glass plates of 1 mm thickness are measured directly from spectral phases detected with a spectrally resolved interferometer. Instead of using the fitting method, the 2π phase ambiguity contained in a detected spectral phase is determined by using an assumption that an actual refractive index measured in experiment is almost the same as well-known data of the refractive index. The actual refractive indexes measured with an error less than 8 × 10 −5 are slightly different from the well-known data about the slope and the constant value in the distributions.
Problems of the development of Russian academic journals from authors’ perspective

The authors compare the models of publishing processes in Russian and international academic journals. It is shown that current publishing process beginning with manuscript submission and ending with publication is significantly more attractive in international journals as compared to obsolete Russian approaches. In the context of the increased significance of domestic journals in Russia, comprehension and adaptation of the best international practices are of key importance for obtaining and spreading scientific knowledge.
Information activities in the sci-tech library

The author discusses the reference and search apparatus and the information resources of the Central Scientific and Technological Library in Construction and Architecture. The paper is prepared within the framework of the Government Order within STLC&amp;A profile No. 9101000.0.BB83AA00000 for 2022.
Acquiring and building content of the digital union information resource of the institutions of the Agrarian Sciences Division of Belarus National Academy of Sciences

The authors share the experience of acquiring the Union E-catalog of the institutions of Belarus NAS Agrarian Sciences Division based on the technologies developed by the International Association of Users and Developers of Electronic Libraries and New Information Technologies (ELNIT Association) in compliance with global and national standards and machine-readable formats, using Internet-technologies and IRBIS64 Library Automation System (LAS). The E-catalog is to support discoverability of the institutions’ information resources and to intellectualize user services. IRBIS64/128 technological capabilities are discussed; the project status and further prospects are analyzed.
Sentimen Pengguna Twitter Mengenai Isu Kebocoran Data Dengan Algoritma Naïve Bayes

Sensitive data leakage occurs when it is unintentionally made available to or accessed by unauthorized individuals. Sentiment analysis is the process of analyzing text to gather different data from the web and social media in order to obtain opinions from internet users on a particular topic. Sentiment analysis is a branch of Natural Language Processing (NLP) that develops a system for extracting and identifying public opinion from text that is then transformed into structured data. One kind of technique for classifying data is Naïve Bayes. Naïve Bayes uses conditional probabilities to assign labels to instances. This study collects information from tweets sent by Twitter users on the subject of "Data Leakage" and then uses the Naïve Bayes method for sentiment analysis to determine the precision of GaussianNB
Prototype of the Solution with a View to Industrialization

The development of a wheelchair to help people with mobility impairments (PMI) in their daily life is a very important topic that interest researchers. The introduction of new technologies can provide these wheelchairs with very interesting and useful functionalities. However, the proposed functionalities increase the cost of the electrical or the smart wheelchair. The main concern of disabled people is how they can access these advanced services at a reasonable cost. The objective of this paper is to describe the development of an intelligent module for standard Manual Wheelchair (MWC) available in the Algerian market. The proposed solution targets to minimize, as much as possible, the number of modifications needed to transform a MWC to an Electric/Smart wheelchair (EWC/SWC). To this end, a 3D model of the standard wheelchair is designed by using a Computer Aided Design (CAD) tool to test % validate the integration of the smart module. Also, a 3D simulation model of the designed wheelchair navigation and its environment was developed by using Gazebo integrated in the Robot Operating System (ROS) to test % validate the proposed artificial vision for obstacle avoidance module. The results of simulation demonstrate the feasibility of the proposed architecture.
A study on how to operate classes to improve problem-solving ability using learner-centered small group learning

This study is a study on the operation method of programming class method to improve problem-solving ability. Software education needs a way to improve communication skills, creativity, cooperation, and problem-solving skills to recognize and solve complex problems. In this study, classes were conducted in parallel with small group learning and individual learning to improve problem-solving skills. Through small group activities, classes were conducted to facilitate problem analysis, problem design, and algorithm writing through communication with team members, and to improve grammatical understanding and thinking skills of C language code through individual learning. As a result of the survey conducted after the class, it was found that the problem-solving ability of students who actively participated in learner-centered small group activities improved, and as a result, it also affected their grades.
Research on Subjective-type Grading System Using Contextual Connection Relation and Segment Information

High quality evaluation needs the subjective-type grading. However it is not easy as natural language processing. Recently, the morphological and syntactic method has used in this research area, but, can not get the good grading because of absence of good semantic analysis and paragraphic connection analysis. To solve the problem we have to do high quality syntactic-semantic analysis and paragraphic connection relation analysis. This paper suggests the subjective-type question grading system using the paragraphic connection relation and segment information. This system is the hybrid system of word based, syntactic-semantic tree based, and paragraphic connection based grading system. The experiment result of the system shows it has the better result than the word based system and syntactic- semantic tree based system. Thus it shows the paragraphic connection information is a necessity for subjective-type grading. This system will be utilized in Korean subjective question grading and document classification.
Ensuring Cloud Data Security Using the Soldier Ant Algorithm

Cloud computing is evolving as a firsthand archetype of large-scale distributed computing which adds more power to internet technologies. It is a framework aiming at convenient and on-request network access to an organized and shared pool of resources. Security of data transmitted and stored by a third party happens to be the greatest challenge for organizations embracing the technology. In this work, a proposed hybrid algorithm dubbed the Soldier Ant Algorithm (SAA) a blend of the Diffie-Hellman algorithm and Delta Encoding technique (Newton Forward and Backward Interpolation). The motivation obtained is the integration of algorithms for cryptography purposes. The integration makes the proposed SAA algorithm symmetric and also makes the Diffie-Hellman algorithm withstand security threats such as man-in-the-middle attacks. The proposed algorithm establishes a secured connection between the cloud client and the cloud service provider and at the same time secures the data sent to the cloud. A comparative analysis was performed against RSA and ElGamal and indicated that the proposed algorithms’ encryption and decryption time were lower even though it is linear (O(n)).
LEGAL AND THEORETICAL FRAMEWORK FOR SEARCH ACTIVITIES TO DETECT CRIMINAL OFFENCES RELATED TO ILLEGAL CONTENT ON THE INTERNET

The purpose of the article is to study the legal and theoretical framework for search activities to detect criminal offences related to illegal content on the Internet.Results.The article considers and analyses the level of ensuring the regulatory and legal framework for the prevention of illegal content on the Internet, in particular in social networks, the creation of a security mechanism to prevent the impact of illegal content on children, as well as the identification of persons who distribute illegal content.The article reviews scientific researches on tactics of detection of criminal offenses, carried out in several areas, and proves that mainly researchers in tactics of detection of criminal offenses distinguish two levels: operative-search and investigative, in accordance with which they consider the methodology of pre-investigative operative-search acquisition and accumulation of primary (intelligence) information to initiate an investigation (about criminal activities) and direct investigation methodology.Conclusions.According to the results of scientific research, the subject of which were separate issues related to the detection system of the analyzed category of criminal offenses, forensic support for the investigation of criminal offenses committed with the use of information and telecommunication systems, the issue of legal protection of social relations in the field of the undisturbed functioning of such systems, as well as operational provision of combating the specified types of criminal offenses, it is worth concluding about the need for further research and scientific resolution of theoretical and organizational tasks that arise during the detection of criminal offenses related to the circulation of illegal content on the Internet.
The Human Touch

To ensure a seamless user experience and to protect their bottom line, manufacturers should implement automated human-like testing of touchscreen user interfaces at every phase of a product's development cycle, says OptoFidelity.
Transformation of education in a foreign language digital environment

The article describes the practical implementation of an experimental model for shaping professional and universal competences of non-linguistic students of humanities in a digital environment of a regional university. It analyzes the ongoing transformation of the educational process, roles and functions of students and teachers. The urgency of the research is determined by the need to find new effective pedagogical technologies for forming competences, which are in demand in knowledge economy. Theoretical and methodological analysis, empirical observations prove that there is a need for a paradigm shift of the educational process in Russian universities, including the development of student collaborations potential in the digital educational environment. The described five-year study involved 46 students of Petrozavodsk State University. Formalized open- and closed-ended questionnaires, as well as observation, expert assessment and statistics methods were used. A model of teaching foreign languages in a digital environment based on teamwork and self-organization is presented. It includes three modules. The first module involves the creation of a competitive foreign-language environment that encourages the development of leadership qualities and self-presentation skills through participation in digital competitions, festivals and language olympiads. The second module is aimed at forming teamwork skills, developing dialogic communicative skills, expanding the communication space for a more natural language socialization of students in professional and socio-cultural discourse. The third module allows organizing group work between students, as well as between students and teachers. The technology of creating a professionally oriented website in English by master's and bachelor's students is described. The results confirm that learning in such a model contributes to the transformation of the roles and functions of teachers and students, leading to a change in their interaction. This, in turn, not only stimulates the development of students' soft skills (such as communicative and digital skills, teamwork, leadership, systemic and critical thinking), but also creates conditions for the implementation of their initiative, creativity and new ideas. The authors conclude that the proposed model contributes to the development of a new method of teaching a foreign language in the digital environment and helps students to socialize in their future profession.
A Study on Machine Translation of Korean Idioms: focusing on {‘ma-eum’ + predicate}

This study attempted to examine how items classified as idioms in Korean are translated through machine translation based on artificial neural networks. in the standard Korean dictionary The results of 14 items presented as idioms translated into English through Google Translator, Kakao Translator, and Papago Translator were compared focusing on the equivalence of the semantic and morphological aspects. This study looked at how the corresponding items were realized in the translation of the title words and examples, and whether the result of the title control translation was applied to the example translation, that is, the result of the title control translation and the result of the example translation were consistent in the same translator. In order to confirm the accuracy of the results translated into English, a BLEU evaluation was conducted to compare them with back translation and human-performed translation. Based on the results of this analysis, the results derived according to the translator were compared, and the types were classified based on form and semantic relevance. The significance of this study can be found in that it suggested the direction of the parts and utilization measures that machine translation should supplement to contribute to improving the quality of the translator through various aspects of the translation results.
About the ‘-e Ju- construction of that I use to myself -Focused on vlog register

In this study, the agent and the beneficiary are the same auxiliary verb ‘Ju-’ in which the agent and beneficiary are same were examined. In this case, when the speaker describes his or her actions, the agernt and the beneficiary are referred to as speaker. When the same context is understood as an instructive act, both agent and the beneficiary are the addressee. This is due to the register of vlog and context of its use. The vlogger’s utterance is understood as both a description and instruction, because the vlog is communicative even though the usage is disconnected, In this context, ‘jupnida’ tend to be fixed in the form ‘ju-’ and does not combined tense elements. By introducing the syntactically redundant beneficiary argument, the objectivity of the utterance is secured the speaker’s actions are expressed to be beneficial. Also, politely express the directivity of instructive speech.
Blended Teaching Evaluation Index System Based on AI Emotion Recognition

With the continuous development of information technology, the teaching method is not limited to offline teaching.Online teaching is on the rise, and more and more teachers use a blended teaching evaluation system that combines online and offline to carry out classroom teaching.However, during online teaching, teachers cannot remind students when students are not paying attention, resulting in low classroom quality.This paper applied artificial intelligence (AI) emotion recognition technology to the blended teaching evaluation index system.When students are studying in the course, the emotion recognition is carried out on the students; when the students are not concentrating, the students are reminded to ensure the quality of the students' learning.Through testing different classes it was found that: the application of AI emotion recognition technology to the blended teaching evaluation system can improve the quality of classrooms, and improve students' learning status and student performance.Student satisfaction had increased by 9.7%, and AI emotion recognition technology can optimize the evaluation index system of blended teaching.
Large-scale image classification with multi-perspective deep transfer learning

Most research efforts on image classification so far have been focused on medium-scale datasets. In addition, there exist other problems, such as difficulty in feature extraction and small sample size. In order to address above difficulties, this paper proposes a multi-perspective convolutional neural network model, which contains channel attention module and spatial attention module. The proposed modules derive attention graphs from channel dimension and spatial dimension respectively, then the input features are selectively learned according to the importance of the features. We explain how the gain in storage can be traded against a loss in accuracy and/or an increase in CPU cost. In addition, we give the interpretability of the model at multiple scales. Quantitative and qualitative experimental results demonstrate that the accuracy of our proposed model can be improved by up to 3.8% and outperforms the state-of-the-art methods.
Content-only attention network for social recommendation

With the rapid growth of social Internet technology, social recommender has emerged as a major research hotspot in the recommendation systems. However, traditional graph neural networks does not consider the impact of noise generated by long-distance social relations on recommendation performance. In this work, a content-only multi-relational attention network (CMAN) is proposed for social recommendation. The proposed model owns the following advantages: (i) the comprehensive trust based on the historical interaction records of users and items are integrated into the recursive social dynamic modeling to obtain the comprehensive trust of different users; (ii) social trust information is captured based on the attention network mechanism, so as to solve the problem of weight distribution in the same level domain; (iii) two levels of attention mechanisms are merged into a unified framework to enhance each other. Experiments conducted on two representative datasets demonstrate that the proposed algorithm outperforms previous methods substantially.
Prediksi Persentase Body Fat Menggunakan Algoritma CART dan M5’

Body Fat Percentage (BFP) is a measurement of total body fat that is used as an accurate measurement for the diagnosis of obesity. BFP measurement is sometimes difficult and inconvenient to perform, even though the picture of BFP’s value is very important for someone to find out the chances of being obese. To overcome this, data mining techniques can be used to measure the predictions of BFP values in a more practical way. This study implements data mining techniques, namely the CART and M5’ algorithm to predict a person's BFP value based on his/her body measurement. The CART algorithm uses the sample average values at leaf nodes to make numerical predictions, while the M5' algorithm builds a regression model for each leaf node with a hybrid approach. Regression trees provide a simple way of explaining the relationship between features and numerical results, but more complex model trees also provide more accurate results. In this study, the results show that the M5' algorithm is superior to the BFP dataset with a correlation value of 0.86 and an MAE value of 3.86.
PROMISE: A QR Code PROjection Matrix Based Framework for Information Hiding Using Image SEgmentation

As data sharing increases explosively, such information encoded in QR code is completely public as private messages are not securely protected.This paper proposes a new 'PROMISE' framework for hiding information based on the QR code projection matrix by using image segmentation without modifying the essential QR code characteristics.Projection matrix mapping, matrix scrambling, fusion image segmentation and steganography with SEL(secret embedding logic) are part of the PROMISE framework.The QR code could be mapped to determine the segmentation site of the fusion image as a binary information matrix.To further protect the site information, matrix scrambling could be adopted after the mapping phase.Image segmentation is then performed on the fusion image and the SEL module is applied to embed the secret message into the fusion image.Matrix transformation and SEL parameters should be uploaded to the server as the secret key for authorized users to decode the private message.And it was possible to further obtain the private message hidden by the framework we proposed.Experimental findings show that when compared to some traditional information hiding methods, better anti-detection performance, greater secret key space and lower complexity could be obtained in our work.