Reviewerly/exHarmony huggingface dataset:
The social mandate of the holistic/integrated approach to learning

The specific elements in the ontological planning of the social require the holistic approach of the social process, but also of the educational ones. The whole-part dichotomy as a relationship of complementarity raises the issue of the specificity of learning integration, starting from the educational purpose, marked by the formation of key competencies, recorded by knowledge, skills, attitudes. The current status of integration, of the action to make something full, complete, very complex, generates a series of renovations, including the issue of this article, focused on the idea of the need for a model of bio- (or eco-) functional integration, designating a useful process for the student in the sense of his real life or his concrete environment.
REAL TIME EYE-TRACKING FOR PASSWORD AUTHENTICATION

Real-time eye tracking is vital for hand free blink-based password entry. PIN’s (password authentication numbers) are extensively used for security and authentication. PINs are largely used for safety reasons. Password authentication works when a user enters the password using his hands, which might lead to cracking the password through techniques like shoulder surfing or thermal tracking. Authentications with eye blink techniques, does not leave any traces behind as there is no movement or contact with the keyboard during password entry and thus provides a safe environment. Eye tracking helps in locating the image frames sequentially and tracks the center of the eye. This project introduces an application in which we are combining eye blink tracking PIN entry, face detection/recognition and OTP (One Time Password) to avoid shoulder surfing and thermal tracking attacks.
EFFECT OF NAOH CONCENTRATION AND RESIDENCE TIME ON THE CONVERSION OF REMOVAL OF Ca2+ AND Mg2+ IN SEAWATER CONTINUOUSLY USING AN BAFFLED REACTOR

The aims of this study were to determine the effect NaOH concentration and residence time on the conversion of calcium (Ca2+) and magnesium (Mg2+) removal as impurities. The concentration of NaOH used in this study were 0.05N, 0,1N, 0.15N, and 0,2N. The reactor used in this study is an baffled reactor equipped with air as a stirrer with air flow rates of 10000, 15000, 20000, 25000, and 30000 ml/minute. The ratio between the flow rate of seawater toward the flow rate of NaOH solution in this study was 85ml/minute : 25ml/minute.The results showed that the NaOH concentration and residence time had a significant effect on the conversion of removal of (Ca2+) and magnesium (Mg2+) impurities. The best results were obtained at 0.25N NaOH concentration, residence time of 13,08 minute, and gas flow rate of 30000ml/minute with removal conversion of calcium (Ca2+) of 73.083% and magnesium (Mg2+) of 89.621%.
Three-Dimensional Mesh Steganography and Steganalysis: A Review

Three-dimensional (3-D) meshes are commonly used to represent virtual surfaces and volumes. Over the past decade, 3-D meshes have emerged in industrial, medical, and entertainment applications, being of large practical significance for 3-D mesh steganography and steganalysis. In this article, we provide a systematic survey of the literature on 3-D mesh steganography and steganalysis. Compared with an earlier survey [1], we propose a new taxonomy of steganographic algorithms with four categories: 1) two-state domain, 2) LSB domain, 3) permutation domain, and 4) transform domain. Regarding steganalysis algorithms, we divide them into two categories: 1) universal steganalysis and 2) specific steganalysis. For each category, the history of technical developments and the current technological level are introduced and discussed. Finally, we highlight some promising future research directions and challenges in improving the performance of 3-D mesh steganography and steganalysis.
Research of single object tracking method based on Siamese Network and Level Set

In this paper, we propose a single object tracking method based on a Siamese network and level set to increase the accuracy of object tracking and segmentation while maintaining real-time tracking. First of all, feature extraction and similarity measurement are performed on the object template image and the search image by using the Siamese backbone network based on ResNet. Then the top-down object tracking contour refinement is performed on the feature map using the level set method. Finally, the loss function of the algorithm is defined, and the proposed algorithm is evaluated and compared on the VOT and DAVIS dataset. The experimental results illustrate that the proposed algorithm maintains the real-time performance, and at the same time the accuracy has been significantly improved.
The Search for Life as a Guidepost to Scientific Revolution

The planetary science community should embrace the search for life as a prime organizing science principle of the decadal survey.The discovery of life beyond Earth, particularly in the form of extant life within the solar system, would be a discovery of such significance that it would be a discontinuity in human knowledge-a scientific revolution.The National Academies' Astrobiology Strategy (National Academies 2019) outlined practical steps that the planetary community should follow to pursue this goal.The planetary community should also prioritize in-situ and, ultimately, sample return missions focused on the habitable environments in our solar system, and work closely with the astronomy community on the detection of habitable exoplanets.Ambitious mission goals need not require ambitious mission budgets.A comprehensive search for life must find ways to diversify its efforts beyond flagship missions into mid-and small-class programs in order to increase mission cadence and thus the potential for biosignature detection.The search for life in our solar system presents a unique opportunity, if embraced by the planetary science community, to implement a clear, encompassing strategy that integrates multiple scientific disciplines and solar system destinations.If life exists to be discovered, the outcome would be, at minimum, historic and, at maximum, revolutionary to the applied sciences of biology and medicine.We have the capability.We know where to look.The time is right.
Transfer Learning Algorithm for Object Detection

This study is related to transfer learning in Faster-RCNN, which is a representative model for object detection tasks. Image recognition includes image classification, object detection and image segmentation task. Transfer learning is especially important for the object detection task and the image segmentation task because of the high cost of generating training data. In this study, we use an algorithm to calculate the difference between tasks by focusing on the amount of parameter updates. We then applied the algorithm to an object detection task and aimed to make it useful for transfer learning.
Challenges of Human-Computer Interaction in Foreign Language Teaching: The Case of a Russian Technological University

This paper focuses on the analysis of the challenges of human-computer interaction as observed while teaching foreign languages at Kuban State Technological University (Krasnodar, Russia). The principal identified challenges can be divided into three groups: 1) the products of computer technology legally available for conducting classes of foreign languages are often insufficient due to various reasons, such as financial and bureaucratic restrictions; 2) language teachers may not be ready to use computer hardware and software properly, even if they want and even have to use them for their classes; 3) students, especially those whose foreign language level is as low as their motivation to master the language, often use computers improperly, imitating language skills rather than developing them. Such challenges need to be properly dealt with so that the benefits of human-computer interaction could be maximized.
Face-GCN: A Graph Convolutional Network for 3D Dynamic Face Identification/Recognition

Face identification/recognition has significantly advanced over the past years. However, most of the proposed approaches rely on static RGB frames and on neutral facial expressions. This has two disadvantages. First, important facial shape cues are ignored. Second, facial deformations due to expressions can have an impact on the performance of such a method. In this paper, we propose a novel framework for dynamic 3D face identification/recognition based on facial keypoints. Each dynamic sequence of facial expressions is represented as a spatio-temporal graph, which is constructed using 3D facial landmarks. Each graph node contains local shape and texture features that are extracted from its neighborhood. For the classification/identification of faces, a Spatio-temporal Graph Convolutional Network (ST-GCN) is used. Finally, we evaluate our approach on a challenging dynamic 3D facial expression dataset.
Research on intelligent risk early warning of open-pit blasting site based on deep learning

The safety of blasting site in open-pit mine can be greatly improved by risk early warning. Therefore, an intelligent real-time risk early warning method of blasting site in open-pit mine based on deep learning was proposed in this research. The mobile wireless webcams, H.264 video compression algorithm, and real-time transport protocol were applied to achieve real-time video acquisition and transmission of blasting site in open-pit mine. A single-stage deep neural network DG-YOLOv3 was proposed in this research. DG-YOLOv3 is an improvement of Gaussian YOLOv3, among which Darknet41 is used to improve the model’s detection speed and detection accuracy of small targets. To further improve the performance (i.e., speed and accuracy) of risk early warning, the surveillance videos were first split into pictures by frame. Then, the pictures were processed by weighted average grayscale and contrast limited adaptive histogram equalization. Experiments show that the mean average precision of DG-YOLOv3 proposed in this paper reaches 87.45 and the detection speed reaches 56.82 frames per second, which has better accuracy and speed compared with other algorithms. In addition, DG-YOLOv3 has good robustness in complex scenarios. Based on the detection results, the intelligent real-time risk early warning of the blasting site in open-pit mine is achieved finally.
Electronic Health Record to Predict a Heart Attack Used Data Mining With Naive Bayes Method

A heart attack is a medical emergency. A heart attack usually occurs when a blood clot blocks the flow of blood to the heart. Cardiovascular disease is a variety of diseases that attack the body's cardiovascular system including the heart and blood vessels. Cardiovascular diseases (CVD) include angina, arrhythmia, heart attack, heart failure, atherosclerosis, stroke, and so on. To resolving (CVD) is to evaluate large scores of datasets, to compare for any information that can be used to forecast, to take care of organize. The method used Naive Bayes classification because that method can determine target which can be used to answer some questions like whether the patient has the potential for heart disease. After data analyst, authors can use data to electronic health records (EHR).
Generation of response spectrum compatible earthquake seismogram considering phase characteristics of possible earthquake motions of site

&amp;lt;p&amp;gt;For seismic analysis of complex and non-linear structure system, a seismic code recommends a dynamic time history analysis. In these cases, the input earthquake seismograms should be needed, and these input earthquake seismograms must be compatible with design response spectrum and reflect the site seismic characteristics including information about a fault and wave travel path between the fault and the site. The foreshocks, main shock and aftershocks of earthquake measured in the target area can be assumed to be the output signals of the system consisting of the fault and the wave travel path between the fault and the site. Each earthquake seismogram is considered as a amplitude modulated (AM) signal defined by the magnitude (or energy) and phase function with time. The probability distribution function (PDF) of the magnitude and phase function can be evaluated through the statistical and harmonic wavelet analysis of the measured output signals and these magnitude and phase PDFs include sufficient information to generate the possible output earthquake seismograms of the fault and travel path system for a site, which mean the phase and magnitude PDFs represent a site seismic characteristics.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;In this paper, the method to generate the possible design response spectrum compatible earthquake seismograms based on the measured foreshocks, main shock and aftershocks of earthquake is proposed. At first the proposed method generate possible earthquake signals reflecting the phase characteristic of a site, and then modify the magnitude of these earthquake seismograms to determine the response spectrum compatible earthquake motions.&amp;amp;#160;&amp;amp;#160;&amp;lt;/p&amp;gt;
\textit{NewsEdits}: A Dataset of Revision Histories for News Articles (Technical Report: Data Processing).

News article revision histories have the potential to give us novel insights across varied fields of linguistics and social sciences. In this work, we present, to our knowledge, the first publicly available dataset of news article revision histories, or \textit{NewsEdits}. Our dataset is multilingual; it contains 1,278,804 articles with 4,609,430 versions from over 22 English- and French-language newspaper sources based in three countries. Across version pairs, we count 10.9 million added sentences; 8.9 million changed sentences and 6.8 million removed sentences. Within the changed sentences, we derive 72 million atomic edits. \textit{NewsEdits} is, to our knowledge, the largest corpus of revision histories of any domain.
Doing Literature in Korean for Foreign Students: Focusing on the Case of ‘Korean Translation and Writing Course’

This study examined the activities of foreign students in Korean, focusing on the case of ‘Korean translation and writing’ in KFL department of HUFS. This started from the worries about how Korean literature can be lively in university education for foreign students.<BR> For foreign students, ‘Korean literature’ cannot be left in the form of a deformed form, a text that shows Korean texts and Korean social culture. No matter what language it is used, literature is a linguistic text containing various thoughts and feelings of human beings, and has infinite possibilities in itself. Reading such literary works is an act of expanding the radius of life and constantly asking questions about oneself. It is also an act that can indirectly reflect oneself in things that have not been foreseeing and experiencing the possibilities of various lives to face in life. For foreign students, ‘Korean literature’ can have such utility.
Dynamics of educational and professional trajectories in the context of socialization of transformations. Conseptual and theoretical model of research

The Yearbook contains articles of a general theoretical, historical and applied nature concerning Russian education and science.The activities of world-class scientific and educational centers and the sectoral system of international scientific and educational cooperation, various problems of Russian educational organizations, including those related to their optimization, trends in socialization and professional orientation of young people are covered.A number of articles are devoted to international education and training of foreign students in Russia, the use and study of the Russian language in schools and universities of foreign countries.The Yearbook is written for employees of Russian educational and scientific organizations, students and graduate students of sociological and pedagogical faculties, as well as to anyone interested in trends in the development of domestic and international education and science.
WHAT OUGHT TO BE DONE FOR IMPERATIVE LOGIC

This paper presents the logical treatment of imperatives (commands and promises) regarded as actions one rational agent performs in order to compel the other rational agent, by imposing certain obligations on her, to act in a certain way.To talk about the embedded stit-formulas that represent such imperative actions the framework of stit-logic supplied with the ⃝-operator, as it is introduced by J. Horty, is used.We investigate some curious technical details of using the ⃝-operator ranging over the set of agents along with different stit-operators and suggest formulas picturing some properties typical for the usage of commands and promises.We establish several theorems and propositions expressing essential principles of imperative agency and show that these principles differ substantially from their analogs in propositional logic and standard deontic logic (SDL).Finally, we briefly discuss the possibilities of further investigation that embodies such issues as expressing the imperative permission and prevalent embedded imperatives in the given framework.
BraidNet: procedural generation of neural networks for image classification problems using braid theory

In this article, we propose the approach to procedural optimization of a neural network, based on the combination of information theory and braid theory. The network studied in the article implemented with the intersections between the braid strands, as well as simplified networks (a network with strands without intersections and a simple convolutional deep neural network), are used to solve various problems of multiclass image classification that allow us to analyze the comparative effectiveness of the proposed architecture. The simulation results showed BraidNet's comparative advantage in learning speed and classification accuracy.
Training of a modern specialist in the conditions of digital professional education

The current economic situation is characterized by increased risk, uncertainty and dynamism of the modern world. Professional education is seriously affected by these changes, which influences the fluctuations of demand for specialists of different profiles. This demand comes from the direct requirements of the established market and focuses on the development of a specialist’s adaptive capabilities in the modern conditions. A modern specialist has to adapt to the labor market, which is characterized by a sharp reduction in demand for low-skilled workers; the emergence of an elite layer of workers who maintain complex electronic and automatic equipment; a reduction in the number of blue-collar workers and an increase in the personnel engaged in design, processing, marketing; the priority of workers who have skills in handling modern office equipment and computers, who have a good command of foreign languages in the field of their profession; the need for managers who are able to organize team work, plan human and material resources most efficiently; the demand for specialists who are able to work at the level of professional excellence from the first days of their independent activity. The market of educational services is now actively improving, which encourages educational institutions to reconsider their approach to the training of professional personnel. The teacher has to rationally use such teaching methods that will ensure the training of qualified specialists who will become competitive in the labor market. The diversity of these methods and techniques should arouse students’ interest in the educational and cognitive activity.
Integrated Model For Honyaku Learning Process In Japanese Literature Departement Of Andalas University

Honyaku (translation) is a compulsory subject in Japanese Literature Department of Andalas University that aims to make students are able and skillful in translating Japanese text into Indonesian and vice versa.The classroom action research method was used in conducting this research.This method is used not only to solve learning problems in the classroom but also to improve the quality of learning in the Honyaku subject as a part of applied linguistics.The object of this research is the integrated model used in the Honyaku course.Furthermore, this study also discusses linguistic knowledge that can be involved in this learning model, including syntax, semantics, pragmatics and other competencies such as knowledge of Japanese society and culture.The results showed that the integrated model could improve student competence in the field of translation and develop lecturers' professional abilities to innovate in learning activities.
Software/Hardware Co-design for Multi-modal Multi-task Learning in Autonomous Systems

Optimizing the quality of result (QoR) and the quality of service (QoS) of AI-empowered autonomous systems simultaneously is very challenging. First, there are multiple input sources, e.g., multi-modal data from different sensors, requiring diverse data preprocessing, sensor fusion, and feature aggregation. Second, there are multiple tasks that require various AI models to run simultaneously, e.g., perception, localization, and control. Third, the computing and control system is heterogeneous, composed of hardware components with varied features, such as embedded CPUs, GPUs, FPGAs, and dedicated accelerators. Therefore, autonomous systems essentially require multi-modal multi-task (MMMT) learning which must be aware of hardware performance and implementation strategies. While MMMT learning has been attracting intensive research interests, its applications in autonomous systems are still underexplored. In this paper, we first discuss the opportunities of applying MMMT techniques in autonomous systems and then discuss the unique challenges that must be solved. In addition, we discuss the necessity and opportunities of MMMT model and hardware co-design, which is critical for autonomous systems especially with power/resource-limited or heterogeneous platforms. We formulate the MMMT model and heterogeneous hardware implementation co-design as a differentiable optimization problem, with the objective of improving the solution quality and reducing the overall power consumption and critical path latency. We advocate for further explorations of MMMT in autonomous systems and software/hardware co-design solutions.