Reviewerly/exHarmony huggingface dataset:
Cache-Enabled Adaptive Video Streaming: A QoE-Based Evaluation Study

Dynamic Adaptive Streaming over HTTP (DASH) has prevailed as the dominant way of video transmission over the Internet. This technology is based on receiving small sequential video segments from a server. However, one challenge that has not been adequately examined is the obtainment of video segments in a way that serves both the needs of the network and the improvement in the Quality of Experience (QoE) of the users. One effective way to achieve this is to implement and study caching and DASH technologies together. This paper investigates this issue by simulating a network with multiple video servers and a video client. It then implements both the peer-to-many communications in the context of adaptive video streaming and the video server caching algorithm based on proposed criteria that improve the status of the network and/or the user. Specifically, we investigate the scenario of delivering DASH-based content with the help of an intermediate server, apart from a main server, to demonstrate possible caching benefits for different sizes of intermediate storage servers. Extensive experimentation using emulation reveals the interplay and delicate balance between caching and DASH, guiding such network design decisions. A general tendency found is that, as the available buffer size increases, the video playback quality increases to some extent. However, at the same time, this improvement is linked to the random cache selection algorithm.
Few-shot segmentation with duplex network and attention augmented module

Establishing the relationship between a limited number of samples and segmented objects in diverse scenarios is the primary challenge in few-shot segmentation. However, many previous works overlooked the crucial support-query set interaction and the deeper information that needs to be explored. This oversight can lead to model failure when confronted with complex scenarios, such as ambiguous boundaries. To solve this problem, a duplex network that utilizes the suppression and focus concept is proposed to effectively suppress the background and focus on the foreground. Our network includes dynamic convolution to enhance the support-query interaction and a prototype match structure to fully extract information from support and query. The proposed model is called dynamic prototype mixture convolutional networks (DPMC). To minimize the impact of redundant information, we have incorporated a hybrid attentional module called double-layer attention augmented convolutional module (DAAConv) into DPMC. This module enables the network to concentrate more on foreground information. Our experiments on PASCAL-5i and COCO-20i datasets suggested that DPMC and DAAConv outperform traditional prototype-based methods by up to 5-8% on average.
Methodological approaches to the formation of a natural-science picture of the world among students in the context of the implementation of the requirements of the Federal State Educational Standards of Secondary General Education

The article discusses methodological approaches to the formation of a natural-science picture of the world among students of a secondary general education school, taking into account the requirements of the Federal State Educational Standard. The main stages of its formation are determined, the role of conceptual thinking in the development of a scientific worldview is shown, the need for a special organization of the educational process using the verbal-logical method of teaching, the possibilities of cognitive dialogue, interdisciplinary integration of basic natural science concepts for mastering the methodology of scientific knowledge by high school students is noted. An important feature of the scientific picture, which must be taken into account in the process of forming students' ideas about a holistic picture of the surrounding reality, along with overcoming disunity between humanitarian and natural science knowledge systems, is the variability and non-linearity of the modern picture of the world. The following are defined as its characteristics: strengthening of the axiological component, anthropologization of scientific knowledge, expansion of the field of reflection on activities, global evolutionism and synergetics, dominance of open self-organizing systems in the study of complex cognitive constructs, convergence of the methodology of natural and human sciences, verbalization of the scientific picture of the world (clear goal-setting , result orientation, flexibility of dialogic discourse in verbal and speech communication, synthesis of knowledge about aspects of the whole world), etc.
Tsifrovye platformy dlia trudoustroistva vypusknikov: upravlencheskie aspekty na osnove tsifrovizatsii obrazovatel'nykh organizatsii

Managing the process of employment of graduates of educational organizations in the process of digitalization acquires significantly new opportunities. The object of the study is the employment of graduates of educational organizations in the process of digitalization of assets, management of these organizations. Subject of the study: participants in the employment of educational organizations, their interaction through digital platforms. Research methods: systematization, classification, analysis of legal documentation. The study confirms the relevance of the topic, clarified the concept of &amp;quot;graduate of an educational organization&amp;quot;, formed a classification of graduates of educational organizations, systematized the material on digital platforms for the employment of graduates in the Russian economic space, proposed the direction of &amp;quot;supervision as mentoring&amp;quot; for the development of the process of employment of graduates in the Russian educational process.
A multi‐device user authentication mechanism for Internet of Things

Abstract The advent of the Internet of Things (IoT) enables different customized services to ease the day‐to‐day life activities of users by utilizing information attained through the internet connectivity of low‐powered sensing devices. Due to device diversity and resource constraints of participating devices, IoT is vulnerable to security attacks. Consequently, authentication is the fundamental measure for using IoT services in the context of network security. IoT devices’ resource captivity makes designing robust and secure authentication mechanisms challenging. Besides, existing user authentication mechanisms are designed assuming a user always accesses an IoT environment using a particular device. However, nowadays, most users employ multiple devices to access the internet; subsequently, it needs an authentication mechanism to handle this diversity. This paper addresses this limitation and proposes a new One‐Time Password (OTP)‐based user authentication scheme supporting user access from multiple devices in an IoT environment. We verify the proposed scheme using widely used BAN logic, AVISPA tool, and informal security analysis, guaranteeing that our scheme preserves the necessary security features. Comparative performance analysis shows that our scheme achieves comparable computation, storage, and communication costs concerning existing works. Moreover, simulation results demonstrate that the proposed method also sustains satisfactory network performance.
Smart Contracts in Construction from Management to Materials: Acting as a Bridge between the Two

The goal of this article is to demonstrate how smart contracts can be leveraged via blockchain technologies. This will enable us to create a bridge between management and the materials used in the construction industry. It is all too common for construction projects to encounter a number of problems along the way, including a lack of communication between builders, laborers, and vendors. As a result of these issues, the proposed timelines and quality of construction end up being compromised. Oftentimes, stakeholders involved in the project are not quite aware of the quality and quantity of materials that will be used to complete the project. It is precisely this problem that we aim to solve through the use of blockchain technology. As a result of the use of blockchain technology, smart contracts offer transparency and trust to their stakeholders. In order to achieve our primary objective, we intend to leverage the advantages of blockchain. This will enable us to ensure clear visibility of construction materials, deadlines, subcontractors and any other elements that are part of a construction project.
Analysis of English teaching in Jinzhou City-take Yixian High School as an example

Under the background of the new curriculum reform, the importance of English Teaching is becoming more and more prominent, and the teachers are always exploring the efficient English teaching mode. However, with the introduction of the new college entrance examination English reform and the double reduction policy, the disadvantages of the traditional high school English teaching mode of middle and high school English connection fault and other disadvantages have also emerged. Starting with the new college entrance examination reform background, this paper discusses the new scheme of English teaching in Liaoning Province.
An integrated taxonomy of standard indicators for ranking and selecting supercomputers

Abstract Due to the ever‐increasing computing requirements of modern applications, supercomputers are at the centre of attraction as a platform for high‐performance computing. Although various features and indicators for testing and evaluating supercomputers are proposed in the literature, a comprehensive feature set to guide designers in comparing supercomputers and selecting an appropriate choice is not provided. Here, an integrated feature‐based taxonomy comprised of seven indicator groups including passive infrastructure, hardware, software, support and maintenance, service, business, and security features is proposed. Also, a case study using our proposed framework is provided and a comparison between some commercial and research supercomputers including Fugaku's ideal supercomputer, Sharif supercomputer, Aramco supercomputer, and ITU supercomputer is presented. Moreover, here, the authors’ proposed method is compared with the Top500 method, which shows that the authors’ proposed method facilitates the ranking, comparison, and selection of the appropriate supercomputer in various fields by considering various aspects of design and implementation. The ranking results show that Aramco supercomputer, ITU supercomputer, and Sharif supercomputer have 65.9%, 57.6%, and 48.2% of ideal supercomputer points, respectively.
Underwater image enhancement via a channel‐wise transmission estimation network

Abstract Underwater image enhancement for image processing and underwater robotic vision have recently attracted much academic attention. However, in most existing methods, underwater image enhancement is completed with a simple assumption: the attenuation coefficients are unified across the color channels. This assumption leads to unstable and visually unpleasing enhancement results. Moreover, these methods cannot be successfully applied to explore relatively independent transmissions from multiple color channels with complimentary feature information. To address these challenges, a novel channel‐wise transmission estimation network (CTEN) is proposed, which aims to pioneer the exploration of the transmission difference across the color channels in an underwater scene. Specifically, a color‐specific correction module is proposed to automatically quantify the transmission ability of multiple color channels in the underwater environment. Furthermore, a channel‐wise transmission estimation module is designed to simultaneously explore the relative independence of multi‐color channels and estimate the medium transmissions for each color channel, which represents the attenuation degree of different color radiances after reflecting in the water. Then, a novel residual strategy is introduced to integrate these two modules to complete the underwater enhancement. Using the model, the authors are able to provide an answer as to why channel‐wise transmission estimation are better than single transmission estimation and establish a generalization theory to show the effect of the independent transmission estimation model for each color channel. Experiments on several underwater image datasets verify the superiority of the proposed CTEN model.
Multilingual bi‐encoder models for biomedical entity linking

Abstract Natural language processing (NLP) is a field of study that focuses on data analysis on texts with certain methods. NLP includes tasks such as sentiment analysis, spam detection, entity linking, and question answering, to name a few. Entity linking is an NLP task that is used to map mentions specified in the text to the entities of a Knowledge Base. In this study, we analysed the efficacy of bi‐encoder entity linking models for multilingual biomedical texts. Using surface‐based, approximate nearest neighbour search and embedding approaches during the candidate generation phase, accuracy, and recall values were measured on language representation models such as BERT, SapBERT, BioBERT, and RoBERTa according to language and domain. The proposed entity linking framework was analysed on the BC5CDR and Cantemist datasets for English and Spanish, respectively. The framework achieved 76.75% accuracy for the BC5CDR and 60.19% for the Cantemist. In addition, the proposed framework was compared with previous studies. The results highlight the challenges that come with domain‐specific multilingual datasets.
The higher education system of Russia: A look into the future

Introduction . In connection with Russia»s withdrawal from the European level system of higher education based on the principles of the Bologna Declaration, the question of which way Russian universities should move on has become acute. It is clear that in modern conditions, a return to the Soviet system of higher education is impossible. At the same time, Russian universities have already managed to adapt to a certain extent to the level system of higher education, seeing in it certain advantages caused primarily by a practice-oriented approach providing for the training of specialists for a market economy. Purpose setting . The purpose of the article is to propose possible ways to modernize the Russian higher education system after abandoning the basic principles of the Bologna Declaration. Methodology and methods of the study . The methodological basis of the study was the systems thinking that reveals the essence of the changes taking place and how certain changes can affect the holistic process of functioning of higher education in Russia. Results . To achieve the purpose of the study, a theoretical analysis of scientific, popular science, educational literature on the subject of the study was carried out; analysis of educational and methodological documentation (curricula, basic professional educational programs, work programs of disciplines), regulatory documents (FSES, professional standards, approximate basic educational programs, professional standards, instructional letters of the Ministry of Education and Science of Russia, etc.). The main features of the functioning of Russian universities in the Soviet and post-Soviet periods are considered. Various aspects of the functioning of higher education are touched upon, on which the quality of training of future specialists depends to a greater extent. Conclusion . Further progressive development of higher education in Russia is possible only if all factors affecting the processes taking place within certain university are taken into account. And the main task today should be a collective search for ways to further modernize the Russian higher education system, taking into account the positive experience accumulated by universities in various areas of their functioning.
Anomaly Detection on Video by Detecting and Tracking Feature Points

There is a well-known problem of video sequence analysis when it is necessary to identify and localize areas of abnormal movement of objects. This is necessary to attract the attention of the operator in the process of work or when analyzing the archive of video recordings. One of the solutions is based on tracklet analysis using short segments of the object’s trajectory that characterize its movement over a certain period of time, and then analysis of activity in various areas of the frame. Since the construction of the tracklet and trajectory is based on the optical flow, the quality and performance of the algorithm significantly depend on the choice and configuration of methods for detecting and tracking feature points. We have analyzed various combinations of these methods using the examples of test videos of normal and abnormal activity in a pedestrian zone. The necessity of a preliminary analysis of the methods used when setting up a video surveillance system to solve specific tasks is shown. Suitable combinations of methods are proposed.
An Underwater Image Enhancement Method for a Preprocessing Framework Based on Generative Adversarial Network

This paper presents an efficient underwater image enhancement method, named ECO-GAN, to address the challenges of color distortion, low contrast, and motion blur in underwater robot photography. The proposed method is built upon a preprocessing framework using a generative adversarial network. ECO-GAN incorporates a convolutional neural network that specifically targets three underwater issues: motion blur, low brightness, and color deviation. To optimize computation and inference speed, an encoder is employed to extract features, whereas different enhancement tasks are handled by dedicated decoders. Moreover, ECO-GAN employs cross-stage fusion modules between the decoders to strengthen the connection and enhance the quality of output images. The model is trained using supervised learning with paired datasets, enabling blind image enhancement without additional physical knowledge or prior information. Experimental results demonstrate that ECO-GAN effectively achieves denoising, deblurring, and color deviation removal simultaneously. Compared with methods relying on individual modules or simple combinations of multiple modules, our proposed method achieves superior underwater image enhancement and offers the flexibility for expansion into multiple underwater image enhancement functions.
Information Processing with Stability Point Modeling in Cohen–Grossberg Neural Networks

The aim of this article is to develop efficient methods of expressing multilevel structured information from various modalities (images, speech, and text) in order to naturally duplicate the structure as it occurs in the human brain. A number of theoretical and practical issues, including the creation of a mathematical model with a stability point, an algorithm, and software implementation for the processing of offline information; the representation of neural networks; and long-term synchronization of the various modalities, must be resolved in order to achieve the goal. An artificial neural network (ANN) of the Cohen–Grossberg type was used to accomplish the objectives. The research techniques reported herein are based on the theory of pattern recognition, as well as speech, text, and image processing algorithms.
Research and Practice of the Construction of an Online Education Community in Higher Education for Disabled Individuals

Since the establishment of ‘Careers for the Disabled’, China has been committed to promoting the program. Special higher education for the disabled is regarded as important for the protection of the rights of the disabled and for the achievement of equity and promotion of the development of special higher education. Currently, many colleges and universities in China provide higher education for the disabled. However, special higher education has problems such as a lack of capable teachers, which requires active inter-school cooperation. Thus, we propose the construction of an online education community for the disabled to overcome the existing problems and propose a methody of promoting the development of special higher education to a higher standard.
Meme Discourse as an Object of Linguocognitive Modelling

Introduction . The goal of this study is to gain new insights into meme discourse by reconstructing its linguocognitive model, based on the properties and characteristics of memes, relevant for Internet communicators. Methodology and sources . In order to reconstruct the meme-discourse model the authors combine the method of linguocognitive modelling with the technique of fragmenting the respondents' answers into motivational explications as units of measurement for the obtained data. The meme discourse model is based on the answers of 100 students at I.I. Polzunov Altai State Technical University – “Why do you use memes when communicating?” The choice of respondents is determined by their studying at the Faculty of Information Technology and being advanced Internet users. Results and discussion . Motivational explications of Internet users of why they resort to memes to communicate serve as language material for inferring cognitive foundations for using memes. The most significant cognitive foundation for the use of memes by communicators is the effectiveness of the impact they make (47.3 %). The second cognitive foundation is related to communication productivity: memes help to establish and maintain communication (20,9 %). The third one is the functionality of memes, which facilitates the transmission of content (17,1 %). The fourth one is the format suitable for conveying thoughts and feelings (14,7 %). Based on the concept of discourse, proposed by T. van Dijk and the reconstructed model the authors gain new insights into the nature of meme-discourse. Conclusion. The main conceptual conclusion regarding meme-discourse is that, as a complex communicative phenomenon, it appears to be an important component of sociocultural interaction for its participants. Both the goal and the result of this interaction is to create a positive type of social context maintained and preserved through mutual understanding between the communicants. Memes facilitate finding common points of contact serving as a “package” of positive emotions for communicators’ thoughts and feelings. In this way communicants produce meme-discourse as an actual referential context to share their worldview.