Reviewerly/exHarmony huggingface dataset:
Modern pedagogical technologies in the system of additional professional education

The text of this article reflects the results of theoretical and practical research in the field of equipping the system of additional professional education with the means of modern pedagogical technologies that affect the quality of professional training of future specialists. The most relevant pedagogical technologies are considered separately, and their effectiveness or ineffectiveness is confirmed by means of online questionnaires. Besides, a significant segment of the study is devoted to reviewing and comparing the experience of predecessors in this matter. The role of personality –oriented and competence-based approaches in the system of additional vocational education is revealed and actualized, their individual elements, especially significant for research, are singled out. A special place in the structure of the study is occupied by the chosen key method – online questionnaire, which is based on data provided by more than 150 teachers of the systems of both higher professional and additional professional education. All of them are not geographically tied to one place, in connection with which one can judge the objectivity of their opinions, as well as the vast geography of the dissemination of the research results. This method is one of the most effective and promising methods of scientific analytical and reflective research.
Implementation of Arithmetic Unit for RNS Using 2n + 3 as Base

Choice of a good modulo base number is an important factor in strength of Modular arithmetic used in Cryptography, Digital signal processing (DSP) and in other areas and therefore needs special attention. Existing literature abundantly describes operations with 2n ± 1 as modulo base. The numbers 2n ± 3 are also prime and offer a set of new base numbers for modular arithmetic. In this paper, implementation of modulo 2n + 3 addition based on shifting and distributive law are described. Modulo operation is performed till the final residue is less than 2n + 3. The results are compared with 2n − 3 architectures described in recent literature. The proposed method avoids mapping of bits reported in the earlier work and hence provides an improved architecture for implementation of modular operations.
Fast Object Detection Using a Frame Skip Method

The object detection deep neural network such as the YOLOv3 shows great performance in accuracy. However, it requires high computational complexity. This work proposes a method for reducing the overall complexity of the object detection on a video stream. For each frame of the input video, temporal subtraction and ORB feature matching is performed between the two consecutive frames to determine whether to perform the YOLOv3 or keep the detection result of the previous frame. The average operation time of the proposed method is reduced to 91.78% on GPU and 59.38% on CPU compared to the YOLOv3 performed on every frame.
An Empirical Study of Pre-trained Embedding on Ultra-Fine Entity Typing

The embedding generated by pre-trained models has attracted the attention of many scholars in the past few years. Most of the context-sensitive embeddings have confirmed the positive impact on some basic tasks of classification, which have only a few types. In this paper, we make an empirical comparison of different pre-trained embeddings on the task of ultra-fine entity typing which has more than 10k types. We apply 7 kinds of pre-trained embedding to the typing model to prove whether the pre-trained embedding has a positive effect. The results indicate that almost all context-sensitive pre-trained embeddings improve the performance of models using Glove. The pre-trained embedding generated by BERT achieves the best performance in the Ultra-Fine dataset and OntoNotes dataset, which shows BERT has better capability to extract finer-grained information than other pre-trained models.
Reduction AWGN from Digital Images Using a New Local Optimal Low-Rank Approximation Method

In this paper, image noise reduction has been formulated as an optimization problem. The target image is denoised using a low-rank approximation of a matrix. Considering the fact that the smaller pieces of the picture are more similar (more dependent) in natural images, therefore, it is more logical to use low-rank approximation on smaller pieces of the image. In the proposed method, the image corrupted with additive white Gaussian noise (AWGN) is locally denoised, and the optimization problem of low-rank approximation is solved on all fixed-size patches (Windows with pixels needing to be processed). Therefore, for practical purposes, the proposed method can be implemented in parallel. This is one of the advantages of such methods. In all noise reduction methods, the two factors, namely the amount of the noise removed from the image and the preservation of the edges (vital details), are very important. In the proposed method, all the new ideas including the use of training image (TI image) obtained from the noisy image, the use of SVD adaptive basis, iterability of the algorithm, and patch labeling have all been proved to be efficient in producing sharper images, good edge preservation, and acceptable speed compared to the state-of-the-art denoising methods.
Interactive Comic Generation Support System with Effect Materials

This paper proposes an interactive comic generation support system with effect materials. In the proposed system, short text with a story and images related to the topic are input, and a comic is interactively generated. It is an interactive system that allows users to select unsatisfied frames and regenerate only those frames after generating comic. It is also possible to regenerate in smaller parts, such as backgrounds, characters, balloons, drawn characters, and comic marks, in the selected frames. This makes it possible to quickly generate comics that are highly satisfying to users. Furthermore, the use of effect materials such as drawn characters, comic marks, and effect lines has been introduced. As a result, more comic-like expressions are possible. Comic is a more effective information transmission method than documents. Through the evaluation experiment, the effect of interactive regeneration and the usefulness by introducing drawn characters, comic marks, and effect lines have been confirmed.
Autopoietic Cognitive Systems in Management Applications

This chapter presents the study of available literature describing autopoietic systems using the systematic mapping study method. Using the knowledge domain visualization technique, the areas of application for management cognitive systems and described therein self-sufficient processes responsible for the success of an organisation were presented. In the study, the research domains considered from the perspective of autopoiesis, such as cognitive computing (CC), information system (IS), communications systems, and Social Systems, were isolated. The study demonstrated that systems implemented based on CC in connection with IS are recommended for management systems. Research confirmed that CC applications using cognitive systems in autopoietic cognitive systems solutions constitute a developing field. Finally, specific and practical applications of cognitive technologies capable of being translated into the economic success of enterprises were indicated.
Methods for Checking Graduate Qualifying Thesis for the Volume of Borrowing

The article is devoted to the issues of checking a graduate qualifying thesis for the volume of borrowed text and the problems of controlling the circumvention of this check. We considered some variants of widely used methods of verification bypass in MS Word documents, a method of the bypass, because of which a large amount of the unique text will take part in the verification. We analyzed various ways of implementing this method in MS Word documents and considered options for software and manual control of this method.
Efficient Deep Face Alignment with Explicit Statistical Shape Models in Convolutional Neural Networks

Face alignment is commonly solved by utilizing a shape representation which is either implicitly learned as in current deep architectures or explicitly given as in active shape models and their derivatives. In this work, we present a method for integrating explicit statistical shape priors into a deep convolutional network by introducing a novel layer which allows using statistical PCA-based models directly in the network, resulting in a highly efficient deep face alignment architecture capable of performing landmark detection with several hundreds of frames per second on consumer hardware. In addition to introducing the core algorithm, we also introduce and discuss extensions for improving fitting precision. We validate the performance of all methods quantitatively on the 300W dataset, where we achieve state-of-the-art precision while requiring only a fraction of the runtime of most competing methods.
Modeling of the Processes of Regulating Energy Efficiency of Technologies and Combining Energy Resources

The article discloses the results of simulating the processes of regulating energy efficiency of technologies by the methods of evolutionary development and jump-like transformations of object technologies in a formed multi-purpose energy technology complex. Organizational and mathematical models of evaluating the energy efficiency of the technologies according to the criteria of the stability of a compromise on the goals of the complex's objects are adapted for regulation. The article demonstrates the applicability of the simulation results to assess the development and transformation processes within the framework of the project of combining conventional and renewable resources. Using waste as the main source of renewable resources can help solve the problems of environmental pollution and energy shortage.
Filtering-Based Correlation Power Analysis (CPA) with Signal Envelopes Against Shuffling Methods

The Correlation Power Analysis (CPA) is one of the powerful Side-Channel Analysis (SCA) methods to reveal the secret key using linear relationship between intermediate values and power consumption. To defense the analysis, many crypto-systems often embed the shuffling implementation which shuffles the order of operations to break the relationship between power consumption and processed information. Although the shuffling method increases the required number of power traces for deploying the CPA, it is still vulnerable if an attacker can classify or group the power traces by operations. In this work, we propose a new CPA technique by efficiently clustering the power traces using signal envelopes. We demonstrate theoretically reduced time complexity and tested our approach with the eight-shuffling AES implementations.
A sensor technology to continuously monitor changes in cognition

Abstract Background Researchers are increasingly utilizing real‐time sensors with ultra‐wideband radio frequency identification device (UWB RFID) technology to continuously, automatically and unobtrusively track the behavior and movement of older adults across care settings (Bowen, Kearns, Crenshaw, &amp; Stanhope, 2019; Bowen &amp; Rowe, 2019; Bowen &amp; Rowe, 2016). These systems can be integrated into the health care environment and are ecologically valid measures taken concurrently as adults perform everyday activities of daily living (ADL). The purpose of this study is to examine the use of a UWB RFID system for the early recognition of behaviors associated with cognitive decline among skilled nursing residents (N=23) of two health care facilities. Method Residents were assessed continuously for an average of 10 months (SD=32.16 weeks). Scoring algorithms from the UWB RFID system utilized 1663 data points developed from x, y coordinates to measure the number and distance (meters) of continuous walking activity in a path. A path is defined as at least 60 seconds of walking and ends with a 30‐second stop. Cognitive function was measured by the Montreal Cognitive Assessment (Nasreddine, et al., 2005) and the Physical and Cognitive Performance Test (Bowen, Rowe, Ersek, Ibrahim, &amp; Shea, 2017). Result On average, residents walked 1522.8 meters/week (SD=1572.7) with an average of 23.2 paths/week (SD=25.6). In multilevel models, accounting for ADL ability, an increased average number of paths per week was associated with decreased cognitive functioning (β= ‐0.65; p≤0.01). Conclusion Continuous walking in a path may be an early indicator of cognitive decline. Using an UWB RFID system may aid in the early detection and recognition of cognitive changes in this patient population. Importantly, these changes are also associated with other health events (e.g., falls, delirium, urinary tract infection, hospitalization) that may be ameliorable to intervention.
Machine Learning based Patient Face Recognition and Medicine Dispensing System using Raspberry Pi

Abstract Machine Learning in healthcare connecting physical devices by exchanging information, Observation and monitoring patient progress and needs. These devices senses collect data and sends symptoms of patient in local database. Proposed system provides patient pills dispenser using raspberry pi. If patient is authorized then dispense medicine if not buzzer alerts. Our project is to make Raspberry pi based Smart medicine dispensing box which uses Machine Learning based patient face recognition. The upcoming feature in our system is that it can monitor the patients ID, depends on ID it recognize patient disease as per previous data base of patient then automatically this dispensing system medicine accordingly. This is reducing the traffic in hospitals and saves patient and doctor time.
Pedagogical tools of eutagology in the higher education system

Abstract The dynamics of the socio-economic sphere development occurs due to the high requirements for the level of training of university graduates. At the same time the level of knowledge at the university does not always suit employers. As a rule, the organization has a need for more experienced and qualified employees. Young specialists who come to work are forced to undergo additional advanced training to develop both professional competencies and over-professional skills. This led to the emergence of the concept of lifelong education, one of the priority areas of which is eutagogics.
Authorship and Scholarly Editing

In his famous lecture “Qu’est-ce qu’un auteur?” Michel Foucault paradoxically refers to the author Samuel Beckett when he quotes the line “Qu’importe qui parle,” which Foucault interprets in terms of indifference. The full quotation is “Qu’importe qui parle, quelqu’un a dit qu’importe qui parle” [“What matter who’s speaking, someone said what matter who’s speaking”]1 – which adds an important nuance. For even though the gist of the line is that the biography of the author may be irrelevant, it does indicate that even the questioning of authorship involves a “speaker” or “writer.” If one chooses not to include biographical research in literary criticism, this usually implies the exclusion of the “bio-” element; but it is harder to ignore the “graphical” facet, the fact that writings are written, by “someone.”
Practical implementation of open science in research projects

The adoption of Open Science (OS) practices is encouraged by different Public Funding Agencies worldwide and, to some extent, has become mandatory within some of the most recognized R&D Research Programs worldwide such as the Program H2020 by the European Commission. In this paper we discuss the experience of two projects working on solar energy research in the adoption of this new way of managing science, one devoted to thermal storage -AMADEUS www.amadeus-project.eu - and the other one devoted to photovoltaic energy -GRECO, www.greco-project.eu-. A brief review of what Open Science means, what practices have been useful for us, what benefits have been obtained and what are the main concerns that have arisen are analyzed in this paper in order to help other researchers in the adoption of Open Science.
Towards a Story Scheme Ontology of Terrorist MOs

Crime investigation and criminal intelligence analysis often rely on the notion of modus operandi. We propose modelling such MOs as story schemes and show how real-life terrorist incidents can be assigned to such schemes. We discuss several requirements of MO schemes and present an implementation in the form of an OWL ontology. This ontology is intended as a conceptual model to be used to support a sensemaking process, whereby crime intelligence analysts populate the ontology with instance data.
Transfer Learning for Neuronal Networks Deployed on the Sensors Edge

The usage of neuronal networks to directly process measurement data recorded by a sensor setup possesses many benefits. However, outside a laboratory application the environment of a sensor must be taken into account for the training phase of the network. This is problematic since many aspects are only known after the installation and therefore are not reflected by the training data. On this account the application of transfer learning is investigated in this work in order to produce a relief for individual installations of mass-produced sensors.
Design and Development Seamless Learning Model to Improve Student Performance in Higher Education

This research aimed to develop seamless mobile android project-based learning to improve student performance. This paper uses the Ghirardini development prototypical and the Information Management Resource Kit (IMARK) (2011). The data analysis used is descriptive quantitative research. The results show: (1) the validation of the media experts have value 87%, and this is included in the very valid criteria; (2) the validation results of the material experts have value 89% and include into the criteria very valid; (3) the outcomes of the validation of the learning expert have value 89% and was included in the very valid criteria; and (4) the results of the practicality test presented that the practicality value of the small group reached 85% and the large group reached 84%, and those percentages are included in the criteria of practicality level is quite valid; (5) the results of the effectiveness test obtained a sig value of 0.000 <; 0.05 so that it can be interpreted that there is a significant effect on student performance.
Cognitive representation of the process of mutual recognition of lecturers and students in the educational space of the university

On the basis of theoretical and methodological analysis, we presented the process of mutual knowledge of the lecturer and student. We considered peculiarities of pedagogical interaction of lecturer and students in educational space of university. The personality, entering into a relationship, better recognizes the interaction partner and inevitably undergoes changes. Therefore, we paid special attention to pedagogical interaction as a sphere of professional implementation and personal development of participants in educational relations in higher education. In the context of pedagogical interaction, the university analyzed the process of mutual recognition of the lecturer and students. We considered the role of the phenomenon of mutual knowledge in social development of personality, formation of collective, preservation of sense of psychological safety. We justified the effectiveness of studying the phenomenon of mutual recognition using the scientific apparatus of cognitive psychology. We presented a cognitive representation of the process of mutual recognition of the lecturer and students, consisting of conceptual representation, frame description and script. This representation allows you to study the dynamic essence of mutual knowledge in more detail and present this process in more detail regarding the lecturer and students, which will help optimize their pedagogical interaction. We revealed the relationship between the personal and professional development of participants in the educational process in higher school and the effectiveness of pedagogical interaction and mutual knowledge of the lecturer and students
Managing Customer Relations in an Explainable Way

We explore how to validate the soundness of textual explanations in a domain-independent manner. We further assess how people perceive explanations of their opponents and what are the factors determining whether explanations are acceptable or not. We discover that what we call a hybrid discourse tree (hybrid DT) determines the acceptability of explanation. A complete DT is a sum of a traditional DT for a paragraph of actual text and an imaginary DT for a text about entities used in but not explicitly defined in the actual text. Logical validation of explanation is evaluated: we confirm that a representation of an explanation chain via complete DTs is an adequate tool to validate the explanation soundness. We then proceed to a Decision Support scenario where a human expert and a machine learning (ML) system need to make decision together, explaining how they used the parameters for their decisions. We refer to this scenario as bi-directional since the involved decision-makers need to negotiate the decision providing explanations. We also address the explanations in behavioral scenarios that involve conflicting agents. In these scenarios, implicit or explicit conflict can be caused by contradictory agents’ interests, as communicated in their explanations for why they behaved in a particular way, by a lack of knowledge of the situation, or by a mixture of explanations of multiple factors. We argue that in many cases to assess the plausibility of explanations, we must analyze two following components and their interrelations: (1) explanation at the actual object level (explanation itself) and (2) explanation at the higher level (meta-explanation). Comparative analysis of the roles of both is conducted to assess the plausibility of how agents explain the scenarios of their interactions. Object-level explanation assesses the plausibility of individual claims by using a traditional approach to handle an argumentative structure of a dialogue (Galitsky and Kuznetsov in International Conference on Conceptual Structures, pp. 282–296, 2008a). Meta-explanation links the structure of a current scenario with that of previously learned scenarios of multi-agent interaction. The scenario structure includes agents’ communicative actions and argumentation defeat relations between the subjects of these actions. We also define a ratio between object-level and meta-explanation as the relative accuracy of plausibility assessment based on the former and latter sources. We then observe that groups of scenarios can be clustered based on this ratio; hence, such a ratio is an important parameter of human behavior associated with explaining something to other humans.