Reviewerly/exHarmony huggingface dataset:
Knowledge Distillation for Action Recognition Based on RGB and Infrared Videos

Most internet videos and surveillance system videos are based on RGB images. In recent years, with the popularization of infrared imagers, infrared images have been gradually used in surveillance systems. The combination of infrared and RGB images brings many advantages to the field of video surveillance. In this paper, we propose a knowledge distillation method based on RGB and infrared videos to classifying person actions. The teacher network is trained by employing RGB videos, and the student network is trained by using infrared data. We learn the RGB action knowledge in the teacher network through knowledge distillation, and reduce the difference between the RGB and infrared modality by narrowing the difference between the significant characteristics of the RGB images and the infrared images. We make an experimental comparison on NTU RGB+D dataset. The outcomes demonstrate that the approach we put forward is superior to the most cross-sectional and most advanced action recognition methods based on infrared.
A Differential Privacy Image Publishing Method Based on Wavelet Transform

Image is an important information-bearing medium with many important attributes. If the image data is released directly, personal privacy will be compromised. This paper aims at how to use the method of differential privacy to protect the privacy of image data and make the image data have high usability. In this paper, a WIP method based on wavelet change is proposed. Firstly, wavelet transform is used to compress the image. Then, noise is added to the main features after transformation to obtain the published image satisfying the differential privacy. It solves the problem of low usability of large images and the problem that Fourier transform cannot deal with abrupt signal. Experimental results show that compared with similar methods in the frequency domain, the denoised image obtained by the proposed WIP method is more distinguishable and the information entropy is closer to the original image. The accuracy is 10% higher than other methods. Compared with other frequency-domain methods for image differential privacy protection, the proposed WIP method has higher usability and robustness.
CHAPTER 10. The Swedish Approach to COVID-19

The Swedish approach to coronavirus disease 2019 differed significantly from that taken by other countries during the first wave, mainly due to constitutional and structural constraints that prevented the kind of strict legally enforced restrictions that were used in other countries. However, over the course of the second wave, the Swedish government changed course, and its actions increasingly came to resemble those taken by other Western countries, with the main difference being that the restrictions in Sweden largely continued to be characterized by voluntarism. The primary reason for this is likely the Swedish constitution, which hindered the government from making most of its restrictions legally enforcible.
Skip Truncation for Sentiment Analysis of Long Review Information Based on Grammatical Structures

In reality, some emotional utterances are especially long, such as the critiques of a movie. Compared with short sentences, the sentiment of a longer paragraph is more difficult to be detected. Moreover, longer paragraphs are eased to overflow the GPU memory and sluggish to fit a large-parameterized network. Currently, the solutions include using a sentence-level summary; if not applicable, a long review is always directly truncated to an accepted length. However, the first solution will ignore the sentiment subtleties; The second solution will lose some important emotive expressions. This work puts forward a strategy to locate the potential sentiment information considering the grammatical structures and then proposes skip truncation to shorten the long review texts. This method can effectively delete irrelevant words without hitting the sentiment skeleton. The new skip truncation is compared against several baselines in binary and multiple sentiment perception. We conduct experiments with four types of standard deep neural networks. Experimental results verify that skip truncation can help reduce sentence length and improve performance in a large margin.
Value-Based Concept in the Architecture Model of a Water Supply Company

The article analyzes the activities of a water supply company, builds an existing model of enterprise architecture, gives suggestions for reengineering the model, and builds a target model of enterprise architecture. When building the target model, the goals of achieving maximum value for the end consumer were taken into account simultaneously with the achievement of maximum results of the enterprise’s efficiency. This work required significant changes and modernization at the application level and the technological level. As a result, a unified system of automated active monitoring and control of the water supply system is being formed.
Machine Learning and IoT-Based Messaging Device for Blind, Deaf, and Dumb People

Recent advances in science and technology have improved the standard of living of human beings and made the life comfortable. But the life of people with visual, speech, and hearing impairments is still uncomfortable in terms of communication. They do not have a proper/simple messaging device that suits their standard of living. The devices that are currently available for them to use have certain limitations in aspects like the cost, simplicity, and limited to vicinal communication. According to reports from World Health Organization, there are about 300 million people who are deaf, 1million who are dumb and 285 million who are blind. This paper describes the device prototype that was designed through which people with visual, speech, and hearing impairments can send messages easily based on their hand gestures. An appropriate machine learning model is used for this task of decoding the meaning of hand gesture that the deaf or dumb person is using. The model was trained on the prepared dataset which consists of the hand gesture images and the corresponding labels. The message decoded by this machine learning model from the hand gestures is sent as mail to the designated person using Amazon web services (AWS), simple email service (SES). This device is mostly suitable for deaf and dumb people compared to blind people in terms of ease to use it.
Blockchain-Based Medical Records System

Health is a critical aspect of a human’s life and so, healthcare is one of the largest market sectors in India and is growing at a fast pace. India’s healthcare industry has been growing at a Compound Annual Growth Rate of around 22% since 2016 and is expected to reach USD 372 Billion in 2022. It produces huge amounts of data in the form of individual health records, among others. There is a crucial need for better management of this data, to make it interoperable while dealing with confidentiality concerns. The four key entities involved in the patient medical records cycle are patients, hospitals, insurers, and government. Until now, electronic solutions to this issue have been centralized, that is, involving a client-server architecture. However, such a centralized architecture faces several drawbacks like risks to failure, attacks, and abuse of power. A blockchain-based system presents a better solution with proper encryption, permission mechanism, and interoperability in such a scenario. In our solution, we use Ethereum blockchain technology and a few others to present a proof-of-concept solution to the stated problem.
RESEARCH ACTIVITIES OF STUDENTS IN PHYSICS LESSONS

Modern changes in the world, the informatization of society, the increasing role of science are making innovations in all spheres of public life. Therefore, the problem of continuous independent education is relevant at the present time. Preparation for independent learning is carried out through the development of cognitive abilities by mastering the methodological apparatus of replenishing and applying knowledge. The age-old methodology of scientific research is an effective tool for solving cognitive problems, as well as for developing creative, communicative and reflective qualities of a person. In this regard, it is very important to introduce students to general and individual methods of cognition of the surrounding world, logic and stages of the scientific cognitive process, in general, to holistic research activities. The article deals with the issues related to the peculiarities of the organization of research activities of high school students of the main school in the process of performing laboratory work in physics. In the course of the study, the analysis of regulatory and legal documents related to the educational process of the primary school, scientific and methodological literature on the problem of research activity was carried out. As a result of the conducted research, the role of the research method in the formation of students ' research skills is revealed. Training based on the model of organizing students ' research activities in laboratory classes in physics was conducted during a pedagogical experiment. 118 students of schools of Taldykorgan took part in the pedagogical experiment. The difference in learning efficiency indicators in the control and experimental groups was evaluated by the "chi-square" criterion. The obtained results showed the effectiveness of the proposed model in the formation of students ' research skills.
Secure Cloud Data Storage and Retrieval System Using Regenerating Code

Since technology started evolving people started using all the latest technology to make them updated and use the technology for their day-to-day life usage. In the exponential growth of technology, cloud computing plays an important role all over to world to store user’s data in it. Cloud storage provides higher storage space for less amount and can access it from anywhere, whenever you want to access the resources. In this paper, they have used a three-layer storage architecture to protect the data from unauthorized users and make the data available to the user’s all the time without any modification in it. The three-layer architecture includes the user local machine, fog layer, and the cloud layer. We propose a system where it provides confidentiality, integrity, availability of the user’s data and we are implementing new techniques like XOR-Combination to fragment and defragment the data and for creating regenerating blocks to retrieve the data successfully, hashing is used to check the integrity of the data while downloading it from the cloud server, block management is used to store the fragmented blocks in the different cloud server to make it secure and keep away it from attackers.
Metamorphic Mineral Reactions Involving Fluids

Building upon the award-winning second edition, this comprehensive textbook provides a fundamental understanding of the formative processes of igneous and metamorphic rocks. Encouraging a deeper comprehension of the subject by explaining the petrologic principles, and assuming knowledge of only introductory college-level courses in physics, chemistry, and calculus, it lucidly outlines mathematical derivations fully and at an elementary level, making this the ideal resource for intermediate and advanced courses in igneous and metamorphic petrology. With over 500 illustrations, many in color, this revised edition contains valuable new material and strengthened pedagogy, including boxed mathematical derivations allowing for a more accessible explanation of concepts, and more qualitative end-of-chapter questions to encourage discussion. With a new introductory chapter outlining the “bigger picture,” this fully updated resource will guide students to an even greater mastery of petrology.
New Paradigms of Technological Digital Design in Industry in Economy Transitivity Conditions

Digital transformation is driving the technological transformations of production. This is especially true for industry, whose share in the country's GDP is quite high. In this regard, the development of a digital technological development contour that provides an optimal way to increase business efficiency in economy transitivity becomes particularly relevant. The purpose of the study was to develop a frontier of technological transformations of production and priorities in the field of advanced production technologies in industry. This study suggested a new framework consisting of digital manufacturing tools used at every stage of the product lifecycle. The map of digital development technologies of industrial enterprises associated with the launch of the innovation and technological cycle is described in detail. The main research method was a foresight methodology based on long-term models of a comprehensive assessment of the development of the global production and technology market in a scenario form. The result of the study is a comprehensive forecast of the development of advanced production technologies and foresight of the priority of technological development in Russia for the modernization of the industrial complex in the conditions of deep penetration of digital technologies, based on the concept of a new industrial society.
The lexical ta’ construction

Fabri (2009) tentatively identifies a number of potential candidates for compound constructions in Maltese. One such candidate, mentioned but not analyzed in Fabri (2009), is the ta’ compound with examples such as tal-laħam ‘the butcher’ and tal-ħobż ‘the bread baker/seller’ (literally ‘of the meat’, ‘of the bread’), which involve the combination of the preposition ta’ ‘of’ with a definite noun. This paper attempts to characterize this construction in terms of its morphosyntactic and semantic (referential) properties. Various types of ta’ constructions are listed and categorized, and the expression tal-laħam ‘the butcher’ is taken as a typical example of the lexical ta’ construction, and explored in great detail. This analysis should serve as a basis for the analysis of other such ta’ expressions.
Incorporating Dynamic Information into Content-Based Recommender System in Online Learning Environment

Learners’ information (e.g., preferences, competencies, contexts) changes over time, which makes it difficult for the recommender system to accurately predict learners’ current needs. Education has higher requirements for recommendation accuracy, especially in online learning environments, it is crucial to accurately understand learners’ current needs and maintain their enthusiasm for learning. We propose an approach to incorporate learners’ dynamic information (preferences, competencies, and contexts) into a content-based recommender system to help learners acquire apposite resources. The system calculates learners’ preferences and competencies from recent learning activities, at the same time, establishes connections between context, concentration, and resource types, makes recommendations more explainable and adaptive.
A Sine Cosine Learning Algorithm for Performance Improvement of a CPNN Based CCFD Model

Nowadays, everyone is habituated of using credit cards for different modes of monetary transactions. This swift acceleration of ecommerce and transaction digitization has shown a comfortable direction to the fraudsters to enact deviant frauds. Only frauds associated with credit cards are being a serious cause of decline in revenue of the country. One way to cease this loss is by promoting efficient credit card fraud detection (CCFD) models. In this article, a CCFD model is built up using Chebyshev polynomial neural network (CPNN). The model performance is enhanced by applying a sine cosine algorithm (SCA) in its training phase. The proposed CCFD model is also compared with two other models on two credit card datasets.
Deep learning Arabic printed document knowledge extraction

This paper presents how to utilize deep learning to extract knowledge from Arabic printed document images. The fundamental goal of deep learning is automatically extracting significant features from images, eliminating the need for a classic feature extraction method. We describe how to extract high-quality and coherent knowledge from Arabic printed document images using deep learning. This system is constructed on keywords used to classify Arabic document images according to these keywords. We used A questionnaire to choose valuable words according to historical, scientific, or religious documents. The evaluation of the proposed system is applied to Arabic printed document images to extract keywords. The accuracy of the proposed deep learning extraction approach is hugely affected by image preprocessing and image quality. The proposed system has a higher level of accuracy while extracting keywords. We achieve a 3.78% character error rate in the proposed system and a 15.46% word error rate.
Towards faster response in virtual reality applications for robotics control

Virtual reality (VR) applications became increasingly popular recently. Their benefits now are not limited by the game and 3D animation software, as industrial VR applications are introduced to control various types of robots and manipulators or to assist in assembling 3D parts of a product either in CAD software or in the factory. However, the main problem with this technology is the high bandwidth requirement, which means some noticeable delay and latency in certain applications. This paper discusses the latency problem in VR-based imitation missions and compares its impact on different imitation systems. The first system uses a Leapmotion sensor as an input device for virtual control of the robot, the second uses HTC VIVE Pro controllers, and the third uses a deep learning hand recognition and tracking system based on VIVE eye cameras. The solutions to this problem according to the different described methods were proposed.
Characteristic of the development of the competence of independent thinking of students in the process of learning in the social and humanitarian sciences

This article highlights the specifics of the development the competence of students’ independent thinking in teaching the social sciences and humanities, their role in the educational process and their importance in the mature of students. The definitions of the concept of independent thinking by various psychologists and educators are analyzed. The main aspects that must be taken into account when developing the competence of independent thinking of a student, and the features of choosing methods for developing independent thinking, are described.
Psychological and pedagogical support for the development of proactive coping with academic stress

The article presents the results of the development and testing of the program of psychological and pedagogical support for the development of proactive coping. The authors of the article define academic stress as a special psychoemotional state that arises in the context of the conditions and requirements of the educational process at a university. Authors consider proactive coping as a way of coping with academic stress - coping focused on anticipating a potential stressor and early accumulation of resources necessary to resolve probable stressful learning situations. The authors suggest that proactive coping can be formed by developing personal coping resources. A proposed support program consist of modules aimed at the development of personal and social coping resources, the formation of educational skills and skills of self-organization. The results obtained in the course of the study prove the effectiveness of the developed support program, which can be included in the curricula and psychological support services of universities.
CRTf-Based Reverse Converter for RNS with Low-Cost Modules $$\{{2}^{n},{2}^{n}-1,{2}^{n+1}-1\}$$

In this paper, we propose a reverse converter from the balanced Residue Number System (RNS) with low-cost moduli set {2^n, 2^n−1, 2^(n + 1)−1} to the Binary Number System (BNS). The proposed method is based on the Chinese remainder theorem with fractions (CRTf) for the reverse conversion device. Constant coefficients are calculated in detail, where the bit width depends only on the value of n. Proposed a device architecture using parallel adders to speed up calculations. Hardware modeling of a reverse converter from balanced RNS with moduli set {2^n, 2^n−1, 2^(n + 1)−1} to the positional number system (PNS) was carried out using the field-programmable gate arrays (FPGA) in the VHDL. The results show that the proposed method achieves a faster performance by an average of 8.5% and lower hardware costs by an average of 10.5% compared to the state-of-the-art method. The proposed development can find wide applications in both digital signal and image processing based on RNS.
Mobile Technology for Learning During Covid-19: Opportunities, Lessons, and Challenges

The Covid-19 pandemic has caused major disruptions to traditional teaching and learning activities globally. As governments continue to develop strategies and policies to tackle the impact of the pandemic on various sectors, teachers are at the forefront of several efforts to ensure that some form of learning and teaching activities are maintained throughout the period, essentially by leveraging on technology. In Nigeria, most of the teachers have not been trained in technology-enhanced teaching and are only able to deliver lessons within the traditional classroom. This paper presents the initial results of a pilot case study of a state government’s response to training teachers in using EdTech to continue teaching during the Covid-19 pandemic. Using a set of criteria based on ease of use, usefulness, and availability, 10 mobile apps were selected and applied to support teaching activities like lesson planning and organization, creation and dissemination of lesson notes, lesson delivery, student assessment, and information management. This paper highlights observations from the pilot training and provides valuable insights into how mobile devices and applications can be used in low-income and resource settings to support educational delivery during a crisis. The paper further provides valuable lessons from the training and challenges to delivery identified by the teachers. Finally, we provide some recommendations to governments and school administrators looking to support the professional development of their teachers with the use of mobile devices.
A Novel Multi-Objective Memetic Algorithm for Mining Classifiers

Genetic algorithm is a nature-inspired evolutionary technique which uses natural evolution methods to explore large solution spaces to find better solutions. Memetic algorithm is a special kind of genetic algorithm that uses a local search technique to exploit the solution space. In the current study, the nature-inspired technique of memetic algorithm is combined with optimization techniques to create a hybrid multi-objective memetic algorithm (MOMA). In the current study, the genetic algorithm is extended into a memetic algorithm by adding a memory base to store the intermediate knowledge and exploit them in the future generations. The algorithm is applied to rule mining as a problem with multiple objectives. The results of testing the algorithm on different data sets is encouraging and throws light in the direction of adding memory to the existing evolutionary computing to get better classifiers.