Reviewerly/exHarmony huggingface dataset:
Bidirectional Integrated Prediction: A Method to Improve the Accuracy of Image Classification

It is a rather challenging task to improve the image classification performance for low-resolution image. To address this issue, we propose a method called Bidirectional Integrated Prediction(BIP), which is simple yet effective in improving image classification accuracy in low-resolution and low-hardware condition scenarios. By considering the outputs of the network for both the original horizontal input images and their horizontally flipped counterparts, our method enhances the performance of various lightweight architectures for image classification. Without employing any training tricks, solely adopting our proposed Bidirectional Integrated Prediction leads to a noticeable improvement in model accuracy. On the low-resolution dataset CIFAR-100 [20], by utilizing BIP, ResNet18 [10] achieves a 0.92% increase in top-1 accuracy, while GoogLeNet [15] improves by 0.58% in top-1 accuracy. Similarly, on CIFAR-10 [20], DenseNet121 [17] reduces the top-1 error rate from 4.34% to 4.3%, and HCGNetA2 [33] decreases it from 4.24% to 4.19%. In addition, BIP also works well on ImageNet [37], with 0.75% increment in the top-1 accuracy of InceptionV3 [30]. We analyzed the effectiveness of this approach and hope that Bidirectional Integrated Prediction can facilitate the application of deep learning in image analysis in various domains, including daily life and industry.
SAC: Dynamic Caching upon Sketch for In-Memory Big Data Analytics

Caching intermediate results in memory, instead of flushing them to disks, actually shortens the completion of big data analytics, because there is no need to reload them for follow-up computations. Constrained by the limited memory, traditional approaches only cache part of the results due to explicit user triggers or simply their accesses, but fail to capture instantaneous system dynamics, including the execution order of parallel stages as well as the current uncompleted dependencies per stage. The data to be cached has to capture such system dynamics and minimize job completion. We thus design a dynamic caching mechanism (SAC) for big data analytics, by using both static sketch upon the stage dependencies in jobs’ preparation and the dynamic adjustment of the such sketch during the job’s execution. The static sketch essentially determines a minimal subset of stages in each job for maximizing the caching benefit while the dynamic adjustment tries to change the caching priority among pending stages. We implement our proposed SAC in Spark, and extensive experiments upon real-world workloads show that the SAC reduces the average job completion by at least 24.6%, compared with those state-of-the-art alternatives.
English Phonology in a Globalized World: Challenging Native Speakerism through Listener Training in Universities in Sweden and the US

English phonetics and phonology often focus on improving learners’ pronunciation. However, phonological processing is ‘a two-way street’ involving both speaker and listener. Thus, pronunciation instruction in this globalized time needs to be complemented with ways to help listeners understand a wide range of accents, thereby challenging the native speakerism and standard language ideology of more traditional English teaching. In this paper, we share our experiences of promoting listener abilities in university courses in Sweden and the US, two very different teaching contexts. In Sweden, Jeong takes a truly phonetic approach, starting from students’ own pronunciations rather than a ‘standard’ model, and focuses on ability to comprehend diverse accents. In the US, Lindemann uses native-speaking students’ complaints about supposedly incomprehensible instructors, not as justification for further training of instructors who are already proficient English users, but as an opportunity to offer listener training to the students. Put together, these experiences provide a basis for Forsberg’s reflection on the teaching of L2 phonetics and pronunciation in other languages such as Swedish, and the benefits of shifting some of the focus from speaker to listener in order to begin to overcome native speakerism and standard language ideology.
Acoustic Fall Detection using Genetic K-NN and SVM

Falls are abnormal movement coordination that forces a person to rest on the ground causing significant health risks involuntarily. This study aims to develop an Acoustic Fall Detection system based on the Genetic K-Nearest Neighbour (ADF-GKNN) feature selection approach and extract significant audio features from spectrogram and Mel Frequency Cepstral Coefficients (MFCCs). The support vector machine classifier is used to identify the falls using the extracted features. The audio signals are extracted from two benchmarked fall video datasets for experimentation. Classification results obtained using the proposed frameworks outperform other feature selection techniques regarding prediction accuracy with 90.6 and 91.8 percentages.
Towards Detecting Influential Members and Critical Topics from Dark Web Forums

Conventionally, the Internet consists of three parts: Surface, Deep, and Dark Webs. Inthe last two decades, a massive increase in illicit activities took place on the differentplatforms of the Dark Web. Moreover, social networks on Dark Web implicateextremism dissemination on a wide scale. In this paper, we propose an approach togenerate textual patterns from discussions on Dark Web terrorist forums employingData Mining techniques. The discovered patterns help identify the influential membersand extract critical topics. We describe our system modules that perform datapreprocessing, text preprocessing with TF-IDF weighting, outlier detection, clusteringevaluation, clustering, and clustering validation, implemented with the RapidMinertool. We apply K-Means as the Clustering method with different distance metrics,evaluate the clustering process using Elbow and Silhouette methods, and validate itusing Davies-Bouldin Index. Furthermore, we investigate the effects of altering thedistance metrics for outlier detection on the Clustering results.
Automatic Text Summarization of News Articles: Recent Advances and Challenges

This survey provides a structured analysis of recent advances in abstractive summarization of news articles using deep neural networks. With the explosion in online news, efficient summarization is critical for consumption and recommendation. We review key modeling innovations including attentional encoders, transfer learning, and controllable generation that have progressed the state-of-the-art. Comparative assessments reveal pre pre-trained transformers now surpass earlier seq 2 seq performance. However, challenges remain in improving coherence, accuracy and semantic evaluation. This timely survey consolidates modern techniques while identifying limitations that motivate future innovations towards production news summarization systems with greater personalization, multilingualism and interpretability.
Integration of IoT and Blockchain for user Authentication

The proliferation of Internet of Things (IoT) devices has ushered in a new era of connectivity, necessitating robust solutions for user authentication to address security and trust challenges. This paper explores an innovative approach to user authentication in IoT environments by leveraging the unique capabilities of Non-Fungible Tokens (NFTs) and 9NM (9NFTMANIA) tokens, with a specific focus on utilizing contract addresses. The proposed system involves the tokenization of user identities through the creation of contract addresses on blockchain networks. Each user is assigned a unique digital identity represented by an NFT or 9NM token, providing a tamper-proof association between the user and their cryptographic keys. Blockchain smart contracts are employed to manage authentication processes, dictating access control policies based on the user's contract address. The research underscores the importance of industry-wide collaboration to develop common standards for user authentication in IoT environments. By offering a comprehensive exploration of user authentication in IoT using contract address-based NFTs and 9NM tokens that are developed on Satoshi core based blockchain, this paper contributes to the advancement of secure and user-centric practices in the rapidly evolving landscape of IoT technology. The proposed framework not only enhances the overall security posture of IoT networks but also lays the foundation for a more transparent and interoperable authentication ecosystem. This paper has discussed the mechanism where web 3.0 based programming is made using Javascript, Python, ASP.NET and PHP for user authentication considering presence of smart contracts in user wallet.
Sensitivity Analysis of Camera using promethee Method

This paper introduces the use of the Analytic Hierarchy Process (AHP) and the PROMETHEE approach for system selection in mining. AHP is employed to analyze and weigh the criteria necessary for decision-making, while PROMETHEE is utilized to rank the alternatives based on sensitivity to changing weights. The study addresses the challenge of measuring the curvature of the plot, using hyper-spears and tangent units in a hypercube. The proposed approach focuses on the selection of inexperienced providers using PROMETHEE and standard criterion priority functions. Comparative results are presented to demonstrate the impact of different preference functions on the final decision. The evaluation considers seven criteria related to financial and environmental aspects. The application of PROMETHEE under the standard preference function reveals that Supplier A1 is the most preferred alternative. The results indicate the dominance of Dealer A1, regardless of skill differences. Furthermore, the paper also discusses the ranking of four different cameras (Camera 1, Camera 2, Camera 3, and Camera 4) based on attributes such as price, zoom, battery, memory, and evolutionary parameter. The PROMETHEE method is employed for this analysis, where Camera 4 is ranked as the top choice, while Camera 2 is ranked last.
A CRITICAL ANALYSIS OF THE DISCOURSE OF NEWSPAPER ARTICLES IN THE ITALIAN LANGUAGE ON THE (NON)PARTICIPATION OF NOVAK ĐOKOVIĆ IN THE AUSTRALIAN OPEN

This paper, within the framework of critical discourse analysis, deals with newspaper articles about the (non)participation of Novak Djokovic at the 2022 Australian Open, published in the electronic editions of the Italian daily newspapers Corriere della Sera and La Repubblica in January 2022. The aim of this paper was to, following Van Dijk (1988a), investigate the schematic organisation of the texts from our corpus, as well as to examine which linguistic units are used in those texts to create a positive and negative image of Novak Djokovic. The results of the research show that a very small number of analysed articles fit into Van Dijk's model of organisation of newspaper texts. The results of the linguistic analysis of the texts indicate that, on the one hand, the discourse strategies of nomination and predication are used to highlight Novak's sporting success, and on the other hand, they serve to portray Novak, who did not receive the vaccine against covid 19, as the culprit for not participating in the Australian Open in 2022 and as a person who behaves recklessly and irresponsibly during the coronavirus pandemic.
The virtual tours of special libraries

While the printed arrays are falling into decline both in the volume and content, advanced and ever-improving software systems process the increasing and dynamical digital data flows much more faster and efficiently. The author suggests that the solution lies in libraries’ expanding functionality. Today, the libraries, including special libraries, have the space available for educational and cultural events, displays, publishing, kids games, well-equipped computer classes and special equipment for the disabled. The authors address the task of website optimization through designing the virtual tour unit.
The new focuses in library information support of science and education

The author analyzes the system of library and information support of science and education in the Russian Federation and the world, and specifies the vectors of its development. The main challenges of the modern society shaping the development of science and education, are discussed, e.g. COVID-19 pandemic, sanctions, Russia’s withdrawal from the Bologna system, and growing digitalization. The status of and prospects for the national/centralized subscription to digital information resources and open access to the full texts of digital scholarly documents are analyzed. The author also addresses the challenges of academic library collection acquisition, university publishing and integrated library systems for academic libraries. The prospects for Russian library information education in the circumstances of Russia’s withdrawal from the Bologna system and increasing digitalization are assessed.
Analyzing microclimate data with IRBIS64 software

The authors discuss the experience of the RAS Library in designing the integrated computerized collection preservation system. They provide the examples of analyzing of the microclimate data for the Library’s depository with two systems, i.e. TKA microclimate control computerized system and IRBIS64. They also discuss in detail the acquisition of the microclimate database with IRBIS64 and further graph plotting for data analysis. The paper is prepared under the Government Order to the Russian Academy of Sciences Library No. 1021051703475-8-2.2.3 for 2022–2024.
Intellectual stimulation and science popularization in scientific libraries in the circumstances of society digital transformation

The author argues that the new forms of academic library services make the natural consequence of society digital transformation and new characteristics of leisure time. Positive and negative expectations for society digital transformation are articulated; related social risks are explored. The background for increasing leisure time is defined; the related dangers are identified. The author suggests that intellectual stimulation and science popularization are the promising vector of services provided by scientific libraries that enable to revise the activities of academic libraries in the current circumstances.
St. Petersburg United System of Library Services. Centralization of information resources

The author discusses the problems of centralized information resources of incorporated public libraries as the case study of St. Petersburg United System of Library Services and its further development.
Informatization, integration and import substitution with IRBIS LAS: Challenges and new opportunities

The author reviews and summarizes on the 2022–2023 situation and its impact on library informatization, implementation of integrated library systems and specialized equipment. He focuses on the key challenges and possibilities based on various options of IRBIS64 Library Automation System and discusses various schemes for implementing IRBIS64 with their advantages and disadvantages. The author provides the examples of IRBIS64 user interfaces and modules applicable for the OS designed in the Russian Federation. He also specifies the key elements of IRBIS64 LAS applied to integrate with other information systems and specialized devices for user services automation.
Artificial Intelligence in education and its application aspects

The definition of Artificial Intelligence (AI) approved by «The National Strategy for Artificial Intelligence Development up to 2030» is discussed. The key vectors for applying AI in education and libraries are explored; its viability for science and education is emphasized.
The main aspects of modern library development in the era of digitalization

The author analyzes the status and trends of informatization. He provides definitions of digitization, digitalization, digital transformation, with the emphasis on the difference between the terms. He also defines artificial intelligence (AI), discusses its history and current state. In librarianship, AI is applied in two forms, in neuronetworks and robotics technology. The development of and prospects for open access to digital resources are assessed. The copyright in librarianship and information sector in the Russian Federation and world countries is discussed. The author concludes that three main trends, i.e. digital transformation, copyright development and Open Access, determine the nearest prospects for library digitalization. The paper is prepared under the Government Order to RNPLS&amp;T No. 075-01235-23-01 of August 17, 2023, R&amp;D theme No. 1021062311368-2-5.8.3 «Development pf electronic librarianship as a scientific and academic discipline in the circumstances of transforming library collections, reference, bibliographic and document services in the digital environment»(FNEG-2022-0004).
The role of modern libraries in promotion of Russian science

The authors summarize the findings of the study of Russian science popularization in the information space. They discuss the models and peculiarities of modern forms of science popularization on the basis of information resources. The role of modern libraries and research centers on Russian science popularization is specified. The paper is prepared within the dissertation study and within the Government Order to VINITI RAN «Development of the concept of science popularization and scientific knowledge management “Russia and global experience”» (No. 0003-2021-0008).
On several aspects of digitalization and digital transformation as the case study of MegaPro Integrated Library Information System solutions

The author examines the practical aspects of digitalization and digital transformation of libraries. He describes Bibliohosting cloud service (SaaS) based on MegaPro automated information library system (ALIS). In particular, the author focuses on ALIS, other systems, services and devices integration and provides examples of the solutions for MegaPro ALIS. The problems of import substitution as related to ALIS are discussed.
PSYCHOLOGICAL AND PEDAGOGICAL CONDITIONS FOR THE DEVELOPMENT OF CONSCIOUS SELF-REGULATION OF STUDENTS OF THE PEDAGOGICAL UNIVERSITY

The article presents the study results of the students’ self-regulation development dynamics in the educational process of the university. The authors consider conceptual approaches to understanding the conscious self-regulation of activity, behavior and mental states of a person, reveal its structural and meaningful characteristics. In the course of analytical work, the article concludes that special attention should be paid to finding the optimal conditions for the behavioral component of self-regulation development. The purpose of the study was to theoretically substantiate and experimentally test the effectiveness of psychological and pedagogical conditions for the conscious self-regulation development among students of a pedagogical university. The choice as a target audience of students of a pedagogical university is due to the fact that this profession requires a future specialist to be able to influence his emotional state and manage his behavior. The scientific novelty consists in the fact that a complex of psychological and pedagogical conditions for the self-regulation development of students has been identified, which ensures in the educational process of the university stimulation of the active position of the person, awareness of its internal resources, and the use of interactive teaching methods as a technological tool. The results obtained during the study can be used in the practical activities of psychological teachers to develop training programs for teachers, undergraduates and students.
IMPLEMENTATION OF DUAL TRAINING AT A PEDAGOGICAL UNIVERSITY

Since vocational education has always been tightly connected with the industrial sector. The authors describe how dual education is implemented in other countries, as well as how the dual education model is being implemented in Kazakhstan. As an example to describe the introduction of elements of dual education, we present the system of dual education of Margulan Pavlodar Pedagogical University. On the whole, we describe the general position on dual education at the university, the main functions of a teacher-mentor, the assessment policy, the features of legal and educational documentation. The paper shows that this technology allows solving the tasks assigned to the pedagogical university for the training of teaching staff for the system of secondary vocational education. The system of dual education is an effective and flexible mechanism that allows you to train highly qualified specialists who are in demand by enterprises in various fields of activity in modern market conditions.
Neural Image Style Transfer Using Modified Histogram Matching

Neural Image Style Transfer is an algorithm which was first introduced in 2016 for transferring the style of an image using a CNN. Over the years, a large portion of the research has been devoted in balancing the trade-off between time taken by the algorithm to process the images and the quality of the results generated. In addition, the application of traditional image processing algorithms has been limited. In this paper, we aim to introduce a modification to the traditional method by utilizing a localized histogram matching algorithm combined with Contrast Limited Adaptive Histogram Equalization (CLAHE). The results show that the quality of style transferred and the colour of images obtained by this method is much better than the traditional method for the same number of iterations.
Pengaruh Variasi Media terhadap Motivasi Belajar Siswa pada Mata Pelajaran Sejarah Kelas XI IPS SMA Negeri 8 Pekanbaru

SMA Negeri 8 Pekanbaru is one of the public high schools which was originally SMPP 49 Pekanbaru and was founded in January 1976 by the minister of Education and culture on November 26, 1975 Number 0261/0/1975. This study aims to determine the effect of the use of media variations on student motivation in the history subject of class XI IPS SMA Negeri 8 Pekanbaru. The type of research used in this study is quantitative type. This research was conducted at SMA Negeri 8 Pekanbaru starting from the submission of the proposal until the completion of the thesis by the author. The use of learning media in history is able to reconstruct the final period that is shrouded in obscurity. The subject of this research was students of SMA Negeri 8 Pekanbaru, namely class XI IPS which collected 100 students. The analysis uses the classical aspect of interest. Media learning history also makes history come alive, clear, and relevant to the lives of students who are oriented to the present or the future. This research was conducted at SMA Negeri 8 Pekanbaru in class XI IPS with a simple of 100 students to fill out a questionnaire or questionnaire that has been provided. The results of this study indicate that the research that has been carried out on the effect of media variations on students’ learning motivations in learning history in class XI IPS at SMA Negeri 8 Pekanbaru, the authors can make the following conclusions, the results of the study indicate that the implementation of media variations in history learning is good, proven by the perception of each student said is a relationship between the media variation program and the motivation to learn history at SMA Negeri 8 Pekanbaru.
APPLYING OF VISUALIZATION TO MANAGE STUDENTS' ACTIVITY IN THE PROCESS OF STUDYING MECHANICAL MOTION

The results of research work are presents.The purpose of work is to activate students by using the educational potential of visualization in conditions of harmonious complement of real and virtual laboratory work in mechanical movement studying process.&#x0D; For the first time in laboratory practice it was possible to successfully create virtual training models similar to real models of physical processes that complement real models using visualization tools and methods, as well as to perform simultaneously visualization of measuring instruments and physical processes within one laboratory task with variable initial data.