Reviewerly/exHarmony huggingface dataset:
TYPOLOGY OF INTELLIGENCE AND LIBRARY LOGO

Intelligence is understood as a means of mental activity, that is, a means of generating, storing, understanding, transforming thoughts in a special intelligible space of the noosphere. Three types of intellects are distinguished depending on the thinking subject: Intelligence A is an individual lively wit of a member of a society, which is in his mind; Intelligence B is a social logos, which is the core of abstract thought and speech sphere of public consciousness (logosphere) and includes the BB Bibliologo as one of its particular types; Intelligence C is an artificial intelligence that exists in a digital virtual reality (computer space and time). Intelligence A is a natural one, operating with symbols (speech and images) in a psychical human world; Intelligence B is artificial, operating with cultural codes in a social environment; Intelligence C is artificial, operating with digital signals in an electronic virtual environment. Two ideological problems are examined: firstly, the problem of the intelligences A, B, C dynamics of development in biological and historical time; secondly, the problem of interaction of various intelligences in the modern society logo sphere. The conclusion that digital culture must be balanced by humanitarian (humanistic) culture, the bearer of which is book cultural heritage, is made. For this, each Russian library should be a center of Russian culture, combining three types of intelligences: 1) library logo; 2) artificial intelligence of free access; 3) lively intelligence of a library team. The educational mission of Library Logos is to use their intellectual potential for to bring to senses (familiarize with the mind) the population of Russia. Moreover, it is desirable that our politicians should comprehend that the library is the humanistic stronghold of the nation, and digitalization (informatization, automation) is an auxiliary tool to strengthen book culture as the basic value of Russia.
Pendekatan Baharu untuk Mengelompok Stesen Pengawasan Kualiti Udara menggunakan Homologi Gigih

The issue of air pollution is a global problem that continues to be discussed today.Often, the use of quantitative approaches such as cluster analysis, correlation analysis and principal component analysis is used to analyze the similarity of air pollution between stations.However, studies related to qualitative approaches, especially topological approaches to analyzing the similarity of air pollution, have not been widely popularized in Malaysia.Therefore, this study is a pilot study conducted to investigate the similarity of air pollution between several stations in Malaysia using a technique in the topological data analysis known as persistent homology.The topological properties of air pollution are described by topological features such as connected components, holes, and void.The particulate matter (PM 10 ) known as the main pollutant is used to describe the air pollution behavior at Klang, Petaling Jaya and Shah Alam air quality monitoring stations.The topological features obtained from the PM 10 is analyzed using distance measure (Wasserstein distance) to obtain topological similarity.The degree of similarity is characterized by a small distance value and vice versa.Results of distance measure show that Petaling Jaya and Shah Alam are the most similar stations and Klang is the most dissimilar station.The validation of these results was carried out by analysis of hierarchical agglomerative cluster analysis that grouped the stations according to their dissimilarity distance and the results are consistent with the findings of this study.From this finding, a more in-depth study using other machinery in the field of topological data analysis can be done as an alternative method for analyzing air pollution problems in Malaysia.
On Data Augmentation and Adversarial Risk: An Empirical Analysis

Data augmentation techniques have become standard practice in deep learning, as it has been shown to greatly improve the generalisation abilities of models. These techniques rely on different ideas such as invariance-preserving transformations (e.g, expert-defined augmentation), statistical heuristics (e.g, Mixup), and learning the data distribution (e.g, GANs). However, in the adversarial settings it remains unclear under what conditions such data augmentation methods reduce or even worsen the misclassification risk. In this paper, we therefore analyse the effect of different data augmentation techniques on the adversarial risk by three measures: (a) the well-known risk under adversarial attacks, (b) a new measure of prediction-change stress based on the Laplacian operator, and (c) the influence of training examples on prediction. The results of our empirical analysis disprove the hypothesis that an improvement in the classification performance induced by a data augmentation is always accompanied by an improvement in the risk under adversarial attack. Further, our results reveal that the augmented data has more influence than the non-augmented data, on the resulting models. Taken together, our results suggest that general-purpose data augmentations that do not take into the account the characteristics of the data and the task, must be applied with care.
Strategies in Case-Based Argumentation-Based Negotiation: An Application for the Tourism Domain

Negotiation is a key solution to find an agreement between conflicting parties especially during the purchase journey. This paper treats the negotiations between a travel agency and its customers in the domain of tourism. Both automated negotiation and argumentation are gathered to create a framework for automated agents, presenting a travel agency and its customers, to negotiate a trip and exchange arguments. Agents take advantage of their past experiences and use Case-Based Reasoning to select the best strategy to follow. We represent agents using two types of profiles, Argumentative profile that represents agents' ways of reasoning and Preference profile that embodies customers' preferences in the domain of tourism.
RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr

Fine-tuning the deep convolution neural network(CNN) using a pre-trained model helps transfer knowledge learned from larger datasets to the target task. While the accuracy could be largely improved even when the training dataset is small, the transfer learning outcome is usually constrained by the pre-trained model with close CNN weights (Liu et al., 2019), as the backpropagation here brings smaller updates to deeper CNN layers. In this work, we propose RIFLE - a simple yet effective strategy that deepens backpropagation in transfer learning settings, through periodically Re-Initializing the Fully-connected LayEr with random scratch during the fine-tuning procedure. RIFLE brings meaningful updates to the weights of deep CNN layers and improves low-level feature learning, while the effects of randomization can be easily converged throughout the overall learning procedure. The experiments show that the use of RIFLE significantly improves deep transfer learning accuracy on a wide range of datasets, out-performing known tricks for the similar purpose, such as Dropout, DropConnect, StochasticDepth, Disturb Label and Cyclic Learning Rate, under the same settings with 0.5% -2% higher testing accuracy. Empirical cases and ablation studies further indicate RIFLE brings meaningful updates to deep CNN layers with accuracy improved.
Instructional Teaching Media to Promote Autistic Student’s Learning Engagement

The demand for students with disabilities to get English lesson underlies the use of instructional media to help teachers to convey instructions as well as students in understanding English. Related to this case, this study aims to describe the types of instructional media used by teacher in SLB Negeri 2 Singaraja to teach an autistic student. The research data were gathered through observation, interviews, and document study. Based on the data obtained, it was found that the teacher used four types of instructional media namely videos, pictures, matching exercise, and real objects. As an implication, instructional media used by the teacher can convey instructions to autistic student even though they did not perfectly understand. Autistic student also understood English lesson better through these media than just listening to the teacher’s speech.
USING GADGETS IN EDUCATIONAL PROCESS: ADVANTAGES AND DISADVANTAGES

The article discusses the use of gadgets in educational process, their advantages and disadvantages are highlighted. It is shown that the use of gadgets allows you to modernize educational process, to make learning more attractive and fruitful.
Usability Evaluation of Islamic Learning Mobile Applications

Abstract : The trend of using mobile devices for the purpose of learning is gaining momentum. Apart from traditional education, various applications are being developed for religious learning. Pakistan is inhabited by around 98% of Muslims. Hence, the informal learning of Islam is essential for Muslim child development. This research presents a usability study of different Islamic learning mobile applications available on the android platform for children. The purpose of this research is to evaluate the usability of different Islamic learning mobile applications for children of diverse age groups in order to understand what design principles must be followed that increase the usability of the application. The main focus of this research is to observe and evaluate how easily children of different age groups respond to different applications, how effectively the children understand the core features of the applications and how easily they are able to use the application by themselves.
Intelligent System of Automatic Shrimp Feeding

Abstract Feeding on shrimp culture is important to the shrimp growth process so that the expected yields are achieved. Feeding must be balanced and timely, there are no advantages or disadvantages in feeding because all the feed provided is not necessarily completely consumed by shrimp, therefore it is necessary to have technology that can control shrimp feeding. Automatic shrimp feed technology can be a solution to the problem of feeding to support the productivity of shrimp culture. Automatic shrimp feeder is built using an arduino microcontroller module, RTC module (Real Time Clock), and feed throwing system. The shrimp feeding method with the working principle of shrimp feeder is shrimp feed thrown horizontally due to centrifugal force. With the influence of the centrifugal force from the propeller spreader, the feed will be thrown throughout the surface of the pond. Feeding is controlled using Arduino by setting the time. Shrimp feeding is done every 4 hours and the appliance is on for 7 minutes to spread 10 kg of feed for the number of shrimps 1,500 and the width of kolan 400 m2 with a minimum throwing distance of feed 1 meter and a maximum of 7 meters.
The Teaching Reform of English Major Translation Course based on the Analysis of Computer Big Data

Abstract At present, in the actual translation process, the English translation work is mostly carried out in the form of teamwork.In the future college English teaching, big data and its related concepts and technologies will become one of the main tools for teachers to find and discover teaching rules, summarize teaching experience and innovate teaching methods, especially in the current English translation courses involving international communication.This paper combines the computer big data technology with the emerging teaching methods such as flipped classroom, and attempts to reform the English translation course for English majors, so as to realize the goal of independent learning and improve the quality of English translation teaching.
Probabilistic Soft Type Assignment

We model randomized complexity classes in the style of Implicit Computational Complexity. We introduce PSTA, a probabilistic version of STA, the type-theoretical counterpart of Soft Linear Logic. PSTA is a type assignment for an extension of Simpson's Linear Lambda Calculus and its surface reduction, where Linear additives express random choice. Linear additives are weaker than the usual ones; they allow for duplications harmlessly affecting the computational cost of normalization. PSTA is sound and complete w.r.t. probabilistic polynomial time functions and characterizes the probabilistic complexity classes PP and BPP, the latter slightly less implicitly than PP.
Central limit theorems for classical multidimensional scaling

Classical multidimensional scaling is a widely used method in dimensionality reduction and manifold learning.The method takes in a dissimilarity matrix and outputs a low-dimensional configuration matrix based on a spectral decomposition.In this paper, we present three noise models and analyze the resulting configuration matrices, or embeddings.In particular, we show that under each of the three noise models the resulting embedding gives rise to a central limit theorem.We also provide compelling simulations and real data illustrations of these central limit theorems.This perturbation analysis represents a significant advancement over previous results regarding classical multidimensional scaling behavior under randomness.
High-End Secure Image Transfer using Vector Quantization

While encrypting data is an explicitly affirmed requirement for many security-based services, the demand for more and more sophisticated and secure ways to store data is rapidly progressing.Images being a rich format of data are being demanded to have better encryption standards resulting in noiseless, visually compromising data.To address this problem, the project adopts an image encryption concept that embeds cipher images into the real data of the host image.A system is manifested through Data Hiding algorithms based on signal processing techniques like vector quantization.Thus, the original image is successfully encrypted and stegonized into the host image.This method of encryption strives at military, judicial, criminal record-based image data transfers where, though any unfortunate data leakages, the decrypting process gets more complex and the meaningful image might mislead the original content from being identified.
THE USE OF GOOGLE ON COMPLETING ENGLISH ASSIGNMENT BY THE STUDENTS’ OF ENGLISH EDUCATION DEPARTMENT AT UNIVERSITAS NEGERI MEDAN

This research is about the use of Google on completing the assignment by the students'. The purpose of doing this research is to find out whether the students use Google on completing their English assignment. It was done at Universitas Negeri Medan exactly in English Education Department. The respondent of this research was the students of 2019 Batch which were taken through purposive randomly sampling. The instrument of this study is a questionnaire which consists of fifteen questions. The result of this study is that that the most of the students (88%) agree to say that they use Google on completing the English assignment and parts of the students (7%) strongly agreed to say that they use Google on completing the English assignment, few of the students (4%) agree to say that they use Google on completing the English assignment for sometimes, and the last is that one of the students were completely disagreed to say that he uses Google on completing the English assignment. Then it is concluded that the students’ perception of Google lies on its practicality, interesting, impact, facilities and impact.
Qualitative Analysis of Monte Carlo Dropout

In this report, we present qualitative analysis of Monte Carlo (MC) dropout method for measuring model uncertainty in neural network (NN) models. We first consider the sources of uncertainty in NNs, and briefly review Bayesian Neural Networks (BNN), the group of Bayesian approaches to tackle uncertainties in NNs. After presenting mathematical formulation of MC dropout, we proceed to suggesting potential benefits and associated costs for using MC dropout in typical NN models, with the results from our experiments.
The role of customer relationship management success factors on enhancing the mental image of telecommunications companies in Jordan

This is one of the first studies of customer relationship management (CRM) in an emerging market of Telecommunications Companies in Jordan.The purpose of this study is to investigate the influence of customer relationship management (CRM) success factors on the mental image among a sample of Jordanian Telecommunications Companies customers.A review of the literature relating to CRM and mental image in both developed and emerging markets was undertaken.The variables which were chosen formed the overall success factors of CRM which are (profitability, knowledgeability, loyalty, attitude, and satisfaction) for enhancing the mental image of telecommunications companies in Jordan.The study sample was selected randomly with a total of 340 citizens by using a quantitative method (questionnaire) to collect data.A 64 percent response rate was achieved.The results revealed the sample held a positive attitude towards the main hypothesis of the study.The variable testing indicated that the most influential variable of the aforementioned on the mental image of the organization appeared through the analysis to be employee attitude as the most influential while profitability appeared to be the least influential variable of all.The researchers recommend the start giving enough attention to the success factors.
Font Recognition of English Letters Based on Distance Profile Features

This paper presents a system for recognizing English fonts from character images. The distance profile is the feature of choice used in this paper. The system extracts a vector of 106 features and feeds it into a support vector machine (SVM) classifier with a radial basis function (RBF) kernel. The experiment is divided into three phases. In the first phase, the system trains the SVM with different Gamma and C parameters. In the second phase, the validation phase, we validate and select the pair of Gamma and C values that yield the best recognition rates. In the final phase, the testing phase, the images are tested and the recognition rate is reported. Experimental results based on 27,620 characters glyph images from three English fonts show a 94.82% overall recognition rate.
Export of Higher Education: Innovations in Physical Education Practice

Creating conditions for the export potential is one of the drivers for the development of the domestic higher education. All the factors of socio-cultural adaptation of foreign students are to be identified in order to build a world-class educational background in Russian universities. The potential of physical education to solve the problems of foreign student integration into the Russian social environment is an urgent area of modern pedagogical research. The article presents the authors’ vision of organizational and pedagogical methods to transform physical education practice at university and to designate some new types of professional teaching activities of a physical education instructor. The research centered in the following Tomsk universities: Siberian State Medical University, National Research Tomsk Polytechnic University, and Tomsk State Pedagogical University. The international component in the educational ecosystem development in Tomsk Region is outlined in the field of the regional project to create the Big University. The applied methods for the research involved analysis of theoretical sources, surveys, observations, product analysis, and the expert assessment method.
Enhancing Reading Advancement Using Eye Gaze Tracking

This research aims to understand the enhancing reading advancement using eye gaze tracking in regards to pull the increase of time interacting with such devices along. In order to realize that, user should have a good understanding of the reading process and of the eye gaze tracking systems; as well as a good understanding of the issues existing while using eye gaze tracking system for reading process. Some issues are very common, so our proposed implementation algorithm compensate these issues. To obtain the best results possible, two mains algorithm have been implemented: the baseline algorithm and the algorithm to smooth the data. The tracking error rate is calculated based on changing points and missed changing points. In [21], a previous implementation on the same data was done and the final tracking error rate value was of 126%. The tracking error rate value seems to be abnormally high but this value is actually useful as described in [21]. For this system, all the algorithms used give a final tracking error rate value of 114.6%. Three main origins of the accuracy of the eye gaze reading were normal fixation, regression, skip fixation; and accuracies are displayed by the tracking rate value obtained. The three main sources of errors are the calibration drift, the quality of the setup and the physical characteristics of the eyes. For the tests, the graphical interface uses characters with an average height of 24 pixels for the text. By considering that the subject was approximately at 60 centimeters of the tracker. The character on the screen represents an angle of ±0.88◦; which is just above the threshold of ±0.5◦ imposed by the physical characteristics of the eyeball for the advancement of reading using eye gaze tracking.
Assessment of the role of the structural components of the natural cycle textbooks in the organization of their own educational activity by high school students

The approaches to the assessment of school textbooks are examined, the existing practice of experimental examination of textbooks is analyzed, the need for involving students in the assessment of the quality of textbooks to increase the degree of objectivity of assessment is substantiated. The features of perception by high school students and their involvement in the organization of their own educational activities of the structural components of a modern school textbook from a group of natural objects are studied. The textbook is considered as the main means of educational activity; the effectiveness of using it by the student is determined by the qualities of the tool and the student’s personal attitude to the textbook as an instrument of his own learning. The study involved 146 students in grades 9, 10 and 11. Respondents defined their attitude to structural elements (teaching texts, figures, tables, graphs, diagrams, tasks of different types, terminology dictionaries) of eight school textbooks by answering a 24-item questionnaire designed to find out the grade (on a ten-point scale) of different aspects of the structural components of the textbooks that participated in the study. The results of the study allowed to determine the change in the attitude of students to the components of the textbook as the educational level increased: reducing the interest of educational texts and tasks while increasing the simplicity of their perception and almost constant level of their understanding, significantly reducing the role of practical work, educational projects, vocabulary in mastering content sustainable influence on the understanding of the texts of figures, tables, graphs and diagrams. The small influence of the factor “educational level” on the results of evaluating the declarative and procedural components of the textbook structure (less than 50%), the advantage of using Web resources for organizing the student’s own educational activity in the procedural direction at all educational levels is shown. The proposed methodology for assessing the structural components of textbooks by students is a continuation of our research towards the creation of an experimental methodology for assessing the quality of the school textbook.