Reviewerly/exHarmony huggingface dataset:
Digitalization of Russian University Educational Space

At present, education is not only a source of educational services but also the most important socio-economic institution, by means of which knowledge is transferred and a new level of civilization is formed.Each teacher at a modern university is faced with the phenomenon of digital technologies, which in turn are poorly subjected to external control.At the same time, search for indicators of educational institutions efficiency increase.The problem is viewed in the context of understanding of the digital economy in terms of global leadership.This defined the purpose of the study, which is to find factors that influence the formation of the personality of a modern teachera teacher of historyin the process of professional training.This study is based on analytically-synthetic and institutional theoretical approaches and comparative-generalizing theoretical method, as well as on following empirical methods: questionnaire analysis, included observation, interviews, focus groups study.Students of the History Faculty control and the experimental groups 59&58 were involved.The study also involved 35 teachers (aged 29 to 68) in 2018-2019 academic year.As a result of the research, we found a number of risks that influence the formation of the personality of a modern teachera teacher of history.Digitalization of the university's educational space in the preparation of a future teacher leads to the disappearance of live communication and the transfer of implicit knowledge, changing the abilities for empathy, experience and complicity and, forming neurosis, depression, mistrust of others and balanced combination of collective and social-communicative forms of interaction with the active involvement of digital technologies is important.
Studi perbedaan antara strategi pembelajaran survey, question, read, reflect, recite and review (SQ4R) dan strategi pembelajaran ekspositori terhadap kemampuan membaca pemahaman ditinjau dari minat membaca pada peserta didik kelas IV sekolah dasar

This study was conducted with three objectives the first is to find out differences of the student’s reading comprehension ability, taught by using learning strategies namely, Survey, Question, Read, Reflect, Recite and Review (SQ4R) and Expository, the second is to find out the differences of student’s reading comprehension skill with high and low reading interest, the third is to find out the interactions between learning strategies and student’s reading interest towards reading comprehension ability. This study was using a quasi-experimental method. The study scope was the fourth grade students in Laweyan sub-district, Surakarta in the 2018/2019 school year. There are 2 elementary schools as samples of research taken randomly using Cluster Random Sampling technique. The data analysis technique used two-way variance analysis with analysis prerequisite tests.  The significance level used was 0.05. The results of the study showed that there are different result between using SQ4R and Expository learning strategy towards the student's reading comprehension ability, there are differences in reading comprehension ability of students with high and low reading interest, and there is no interaction between learning strategies and student’s reading interest towards student’s reading comprehension ability. Keyword s : Survey, Question, Read, Reflect, Recite and Review ( SQ4R ), Expository, Reading Interest, Reading Comprehension ability, Elementary school
Constructing quantum codes from any classical code and their embedding in ground space of local Hamiltonians

We introduce a framework for constructing a quantum error correcting code from any classical error correcting code. This includes CSS codes and goes beyond the stabilizer formalism to allow quantum codes to be constructed from classical codes that are not necessarily linear or self-orthogonal (Fig. 1). We give an algorithm that explicitly constructs quantum codes with linear distance and constant rate from classical codes with a linear distance and rate. As illustrations for small size codes, we obtain Steane's $7-$qubit code uniquely from Hamming's [7,4,3] code, and obtain other error detecting quantum codes from other explicit classical codes of length 4 and 6. Motivated by quantum LDPC codes and the use of physics to protect quantum information, we introduce a new 2-local frustration free quantum spin chain Hamiltonian whose ground space we analytically characterize completely. By mapping classical codewords to basis states of the ground space, we utilize our framework to demonstrate that the ground space contains explicit quantum codes with linear distance. This side-steps the Bravyi-Terhal no-go theorem because our work allows for more general quantum codes beyond the stabilizer and/or linear codes. We hesitate to call this an example of {\it subspace} quantum LDPC code with linear distance.
Personality. Development of Thought Throughout Time. Existence

Each personality contains a part of the fullness and depth of the World and the completeness of it depends on personality’s own abilities and talents. Each «I» has the right to consider itself valuable and can claim to have a dialogue with another personality. A personality can evaluate and contain various cultures, knowledge and beliefs, science and religions. Each personality actualizes what can be called the development of thought throughout time. Moreover, not only «in the time» in sense of Newton’s and Einstein’s physics, but, mainly, in what we call «the time of the appearance of the Savior», «Shakespeare’s time », «our time». That is, a set of conditions under which historical events occur. All these times are characterized by their own way of thinking and their own level of knowledge. And their own laws of existence. This means not only the factual existence, but also that exists in the imagination of the individual. At the same time, imaginary reality can more affect a person’s worldview than actual reality. The development of thought throughout time brought a lot of useful things to a person, but also a lot of disastrous ones, such as conflicts and wars, global catastrophic risk, world-wide pre-crisis ecology problems, and a lot of other troubles – all these that can direct a person’s thought towards dreams and imagination. Current problems of time, of course, disappear and are absorbed by Eternity. Eternity embraces and completes all time and existence. However, if you connect your imagination, then an inquisitive, free thought can assume the existence of the Pre-Eternal. Absolute, God. Just assume that He controls us, but we must trust Him with many of our concerns. Existence is a fundamental category. You can exist in reality or in imagination…or in the reality of imagination. The author considers the conversation about existence for himself not yet complete...
Image/Video Forensics

Images and videos, which have always had a huge impact upon the way people perceive the world and form their convictions, are pervasive in today’s reality more than ever. Even in the forensics scenario, evidences are more and more often composed by multimedia in general and visual data in particular. Since the new meaning of “original data” in this digital world requires new approaches to ensure the admissibility of these elements as evidence in a trial, starting from the first years of this century the need to prove the authenticity of a digital evidence became crucial. This work introduces the sub area of Digital Forensics, which has the aim to define and develop the procedures devoted to help operators in this challenging research area. After an introductory part, the topic of this paper was introduced, starting from the meaning of digital evidence, and following with the definition of Image / Video Forensics as a branch of the forensic sciences. Then some methods allowing the extraction of significant information from the images when it is not readily available are examined in detail. Finally, a list of free and non-free software devoted to face the daily challenges coming from processing images and videos for forensic purposes is provided. The work ends with a list of publications containing the Best Practices in the field.
Learning-based Low Light Image Enhancement for Visual Odometry

For the low light environment, performing good visual odometry still remains an open challenge. The main difficulties in low light situations lie in that the limitations of the sensors and the buried features in the dark, which hamper to achieve successful detecting and tracking of interest points. Although there are some pioneering works proposed on image enhancement for low light situations, there are comparatively little works focusing on visual odometry in low light scenes. Here, we address this problem from a deep learning view, for which we train a deep neural network for image enhancement to obtain the enhanced image sequences for VO. In contrast to the end-to-end training scheme, the network is designed based on the physical Retinex model, and the L <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> distance loss and structure similarity index measure (SSIM) loss are incorporated into network training. We validate the performance of the enhancement by evaluating the enhanced sequences by state-of-the-art VO algorithm, ORB-SLAM.
Development of Interest in Healthy Lifestyle Among Students

This article analyzes the results of a survey conducted among students of the faculty of Economics of the Vladivostok branch of the Russian Customs Academy. The main topic of the survey is the interest of students in the formation of a healthy lifestyle. During this research the method of the analysis of results of questioning among students and the analysis of the scientific literature reviewing this question was used.
Intrinsic Decomposition of Document Images In-the-Wild

Automatic document content processing is affected by artifacts caused by the shape of the paper, non-uniform and diverse color of lighting conditions. Fully-supervised methods on real data are impossible due to the large amount of data needed. Hence, the current state of the art deep learning models are trained on fully or partially synthetic images. However, document shadow or shading removal results still suffer because: (a) prior methods rely on uniformity of local color statistics, which limit their application on real-scenarios with complex document shapes and textures and; (b) synthetic or hybrid datasets with non-realistic, simulated lighting conditions are used to train the models. In this paper we tackle these problems with our two main contributions. First, a physically constrained learning-based method that directly estimates document reflectance based on intrinsic image formation which generalizes to challenging illumination conditions. Second, a new dataset that clearly improves previous synthetic ones, by adding a large range of realistic shading and diverse multi-illuminant conditions, uniquely customized to deal with documents in-the-wild. The proposed architecture works in a self-supervised manner where only the synthetic texture is used as a weak training signal (obviating the need for very costly ground truth with disentangled versions of shading and reflectance). The proposed approach leads to a significant generalization of document reflectance estimation in real scenes with challenging illumination. We extensively evaluate on the real benchmark datasets available for intrinsic image decomposition and document shadow removal tasks. Our reflectance estimation scheme, when used as a pre-processing step of an OCR pipeline, shows a 26% improvement of character error rate (CER), thus, proving the practical applicability.
The effectiveness of brands awareness through social mediaon modest fashion in Kota Bharu

This study is about creating new knowledge and better understanding on the important of The Effectiveness of Brands Awareness Through Social Media on Modest Fashion in Kota Bharu Kelantan. The main purpose of this study was to use bench-marking to identify concrete actions that can be used to influence brand awareness in social media platforms such as Facebook and Instagram. Consumers’ awareness of a brand is essential, as brand awareness is considered one of the main reasons that brand and its products are purchased. The use of social media has been regarded a great possibility for brands to increase global brand awareness, however, with continuously increasing competition for attention and fast commercializing social media, getting noticed has become challenging. Objective of study is to discover the relationship between brand expose, electronic word of mouth, paid advertisement and customer purchase intention with effectiveness of brand awareness through social media on modest fashion in Kota Bharu.
LibGuides: How to reference for Senior School: Quick Guide: the basics (footnotes & endnotes)

Constructing references for your assignments can be challenging - use this LibGuide to get help for the more common resource types, as well as for help with how to footnote/endnote.
Py_ape: Text Data Acquiring, Extracting, Cleaning and Schema Matching in Python

Py_ape is a package in Python that integrates a number of string and text processing algorithms for collecting, extracting, and cleaning text data from websites, creating frames for text corpora, and matching entities, matching two schemas, mapping and merging two schemas. The functions of Py_ape help the user step-by-step perform data integration and data preparation, based on some popular Python libraries. Especially in the entity matching function of the schema matching and merging phase, we used the Hamming distance algorithm to identify similar string pairs, and the longest common substring similarity algorithm to map data between the columns of schemas. These algorithms help to increase the accuracy of the schema matching process. In addition, in the article, we present experimental results using Py_ape to scrape, clean, match, and merge two sets of data related to aviation crashes, taken from different sources of Kaggle and Wikipedia. The result of the experiment will be evaluated in detail in the rest of the paper.
The role of active aging in preventing depressive symptoms in elderly individuals: an integrative review

Objectives: To describe the relationship between active aging and the presence of symptoms of depression in elderly patients. Methodology: This is an exploratory, descriptive study, of the type Integrative Literature Review, in which data were collected from the virtual research libraries: Online Electronic Scientific Library (SCIELO), Virtual Health Library (BVS), and Latin Literature American and Caribbean Health Sciences (LILACS). Results: It was found that the participation of the elderly in physical activities appropriate for their age group, and social interaction based on cultural events such as: theaters, cinema, museum, galleries, etc., presented itself as a significant variable for reducing the rate of depression. Conclusion: Active aging is an important factor for improving the quality of life in elderly individuals, making it necessary to develop programs in the family health strategy that provide opportunities for social interaction and physical activity in the elderly.
Quality metrics to measure the standards conformance of geospatial linked data

This paper describes three new Geospatial Linked Data(GLD) quality metrics that help evaluate conformance to standards.Standards conformance is a key quality criteria, for example for FAIRdata. The metrics were implemented in the open source Luzzu quality assessment framework and used to evaluate four public geospatial datasetsthat showed a wide variation in standards conformance. This is the firstset of Linked Data quality metrics developed specifically for GLD
Boosting CNN-based primary quantization matrix estimation of double JPEG images via a classification-like architecture

Estimating the primary quantization matrix of double JPEG compressed images is a problem of relevant importance in image forensics since it allows to infer important information about the past history of an image. In addition, the inconsistencies of the primary quantization matrices across different image regions can be used to localize splicing in double JPEG tampered images. Traditional model-based approaches work under specific assumptions on the relationship between the first and second compression qualities and on the alignment of the JPEG grid. Recently, a deep learning-based estimator capable to work under a wide variety of conditions has been proposed, that outperforms tailored existing methods in most of the cases. The method is based on a Convolutional Neural Network (CNN) that is trained to solve the estimation as a standard regression problem. By exploiting the integer nature of the quantization coefficients, in this paper, we propose a deep learning technique that performs the estimation by resorting to a simil-classification architecture. The CNN is trained with a loss function that takes into account both the accuracy and the Mean Square Error (MSE) of the estimation. Results confirm the superior performance of the proposed technique, compared to the state-of-the art methods based on statistical analysis and, in particular, deep learning regression. Moreover, the capability of the method to work under general operative conditions, regarding the alignment of the second compression grid with the one of first compression and the combinations of the JPEG qualities of former and second compression, is very relevant in practical applications, where these information are unknown a priori.
Aspects of Sustainable Development of Russian Regional Universities

Modern universities present themselves as universities implementing the goals of sustainable development. The aim of this paper is to summarize the experience of universities in the world and Russia in the field of sustainable development and to work out a comprehensive program for the development of the Irkutsk National Research Technical University to achieve the goals of preserving the planet and creating a “green campus” taking into account regional aspects associated with the uniqueness of Lake Baikal. The paper considers the experience of a number of European universities and presents the directions of the long-term development program for the Irkutsk National Research University, resulting in the development of the Baikal region. In the work, we also consider aspects of the program taking into account the uniqueness of Lake Baikal.
A decentralized approach towards secure firmware updates and testing over commercial IoT Devices

Internet technologies have made a paradigm shift in the fields of computing and data science and one such paradigm defining change is the Internet of Things or IoT. Nowadays, thousands of household appliances use integrated smart devices which allow remote monitoring and control and also allow intensive computational work such as high end AI-integrated smart security systems with sustained alerts for the user. The update process of these IoT devices usually lack the ability of checking the security of centralized servers, which may be compromised and host malicious firmware files as it is presumed that the servers are secure during deployment. The solution for this problem can be solved using a decentralized database to hold the hashes and the firmware. This paper discusses the possible implications of insecure servers used to host the firmwares of commercial IoT products, and aims to provide a blockchain based decentralized solution to host firmware files with the property of immutability, and controlled access to the firmware upload functions so as to stop unauthorized use. The paper sheds light over possible hardware implementations and the use of cryptographically secure components in such secure architecture models.
Feature Extraction for Software Defect Detection Utilizing Neural Network with Random Forest

Programming deformity expectation is the most pivotal advancement in enormous programming improvement associations where the multifaceted nature of the production task is expanding at an exponential rate. Allotting the right seriousness level to the imperfections experienced in enormous and complex programming undertakings would help the product professionals to assign their assets and plan for consequent deformity fixing exercises. So as to achieve this, we have built up a model dependent on the neural system method with random forest which includes extraction that will be utilized to dole out the seriousness level to each abscond report dependent on the grouping of existing programming module reports. The proposed model is assessed utilizing PROMISE Software Engineering Repository informational indexes. It is clear from the outcomes that the model has performed very well in anticipating high seriousness programming surrenders than in foreseeing the deformities of other seriousness levels.
Numerical Calculation of Two-qubit Rabi Model

The purpose of this paper means to study the numerical solutions of two-photon Rabi model of two-qubit system. We described the Hamiltonian in a collective space of Fock space and spin-1 space. To calculate the dynamics, the initial state is set to a normal squeezed state and we calculate the exact solution of time evolution of the initial state. And a time evolution of average angular momentum is set for examples at the last part of this paper.
스페인어 존재 동사(Haber)와 장소 동사(Estar) 간의 의미적ㆍ구문적 차이에 관한 고찰

The existential verb HABER and the locative verb ESTAR can be used to indicate the presence of a person or thing. But they are seldom interchangeable in Spanish. The subtle differences between these two words can completely change the meaning of a sentence. In concrete, the difference mentioned is that the verb HABER is used to indicate the mere existence of the person or thing. On the other hand, ESTAR is introduced to indicate the location of the person or thing. As a general rule, the locative verb ESTAR is permitted when a specific person or thing is referred to, however the existential verb HABER is used with nouns that can’t have a location. As a result, a noun preceded by a definite article, a demonstrative adjective or a possessive adjective normally would be introduced with the verb ESTAR. The locative verb ESTAR y the existential verb HABER can be used in situations where “to be” is used in English. So they’re usually confusing for students. In this paper, we have argued that the existential verb HABER is derived from the copulative structure. In this point of view, the locative verb ESTAR is defined by the spell-out of the event feature.
COLLABORATIVE TUTORING: A MULTI-TUTOR APPROACH

Abstract. An Intelligent Tutorial System (ITS) is a learning computer environment. Many ITSs do not integrate human tutor since they are designed to use in autonomy by the learner. One of the reasons to increase the rate of desertion in a distance training framework compared to that of a face-to-face course is the absence of the human killer. Besides, the existing ITSs are dedicated to a single learning object based on domain-dependent modelling. Our contribution consists in proposing an ITS, independent of the learning domain, capable of initiating learning, of managing an articulation between machine tutoring and human tutoring (teaching and peers) to offer an individualized and personalized follow-up, and ensure certification of the learner’s assessment.