Reviewerly/exHarmony huggingface dataset:
THE LIBRARY OF THE BARNAUL GYMNASIUM OF M. F. BUTKEVICH AT THE BEGINNING OF THE 20TH CENTURY AND ITS ROLE IN THE FORMATION OF A VERSATILE PERSONALITY

The article deals with the problem of identifying and studying book collections of educational institutions of the Altai district at the beginning of the 20th century. Using the example of books from the library of the Barnaul private women's gymnasium, established by M. F. Budkevich, which are kept in the department of rare books of the Altai Regional Universal Scientific Library named after V. Ya. Shishkov, the book fund is analyzed as an integral part of the educational process. Archival materials from the fund of the State Archive of the Altai Krai are involved, allowing to clarify the quantitative characteristics and the type of composition of the book fund in different years of the gymnasium. The information about the sources of replenishment of the library's fund in 1908–1919 is given, the owner's book signs are presented. The presence in the library's collection of not only textbooks, but also popular science literature testifies to the formation of the intellectual potential of students, stimulating their cognitive activity. The conclusion is made about the essential importance of the library collection of the Barnaul private women's gymnasium as a valuable source for the study of book culture, the history of the development of enlightenment and gymnasium education in Altai.
Overview of Neuromorphic Optical Systems

After analyzing in Chap. 1 some of the most important features of the biological brain that underlie learning process and information storage, this Chapter provides a quick overview of optoelectronic and fully-optical neuromorphic techniques implemented to date. The operation and physical principles of each approach presented is described. These are grouped into three main categories called paradigms. Each neuromorphic paradigm is built on a main neural connotation. The first paradigm replicates neural excitability. The second paradigm focuses on the concept of connection between units. Finally, the third paradigm is an absolute novelty in the scientific panorama and encompasses only solitonic networks, which can replicate a tissue structure. The main difference from other neuromorphic hardware lies in their ability to self-organize according to the received stimuli, evolving accordingly over time.
Revisiting Class Imbalance: A Generalized Notion for Oversampling

Abstract Class imbalance is a salient problem in both machine learning and data mining realms. Sampling techniques have become a cornerstone in solving this challenge, as they enable the creation of class-balanced datasets that is essential for robust model training. Addressing class imbalance not only enhances the predictive accuracy of machine learning algorithms but also ensures fair and unbiased decision-making across various applications, making it a critical aspect of research and development in various sectors. Through this work, we introduce the concept of a generalized oversampling function, unifying existing synthetic oversampling approaches. We explore diverse design decisions for such a function, presenting six functions categorized as linear and non-linear variants. We provide extensive experiments with these functions to gain an in-depth understanding of their behavior. Through our experiments, we observe that the best-performing function is primarily data-driven. Also, it is perceived that non-linear functions like minimum and maximum often depict higher learning capacity and steady performance in comparison to their linear counterparts mainly due to their ability in modelling non-trivial patterns. While moderate input counts would yield desirable performance in these functions, we can see varying robustness from these functions for distorted input data.
EXPLORING TUTORS’ STRATEGIES IN TEACHING SPEAKING AT PPB IAIN SYEKH NURJATI CIREBON

This study, which includes an English tutor and 30 students in the third semester of the class PPB IAIN Syekh Nurjati Cirebon, aims to portray tutors’ tactics in teaching speaking to PPB IAIN Syekh Nurjati Cirebon and recognize the effects of strategies used by the English tutors. To determine the speaking instruction methodologies, interviews, and classroom observations were undertaken as part of the data collection. The outcome showed that the tutors’ methods included drills, role-plays, speaking lines, and discussions. As a result of the teacher's speaking techniques, pupils get more engaged in their studies, develop more optimistic outlooks, and become more motivated. Almost all of the students prefer the speaking lines as the method of teaching speaking among the three tactics used by the teacher because they believe it can enhance their speaking skills, increase their desire to talk and make the teaching-learning process more enjoyable.
Babbling stochastic parrots? On reference and reference change in large language models

Recently developed large language models (LLMs) perform surprisingly well in many language-related tasks, ranging from text correction or authentic chat experiences to the production of entirely new texts or even essays. It is natural to get the impression that LLMs know the meaning of natural language expressions and can use them productively. Recent scholarship, however, has questioned the validity of this impression, arguing that LLMs are ultimately incapable of understanding and producing meaningful texts. This paper develops a more optimistic view. Drawing on classic externalist accounts of reference, it argues that LLMs are very likely capable of reference. Not only that: The combination of a popular externalist account of reference and recent experimental data in machine psychology even suggests that LLMs might play a role in shifting what our words refer to.
SCOUTING AS AN EFFECTIVE MEDIA FOR YOUNG GENERATION CHARACTERBUILDING:TALCOTTPARSON'SSOCIALSYSTEMS THEORY

Thisarticleillustrateshowscoutingpracticescanhaveapositiveimpactonthecharacter-building of children and youth using Talcott Parson's social systems theory. Scouting provides hands-on experience through outdoor activities, community service, and learning practical skills. This article also highlights the important role of scout leaders who provide positive role models and guidance and reinforce scouting values. In this paper, the research approach applied is using literatureanalysis,referringtosourcesfromaccreditedjournalsatbothnationalandinternational levels. The focus of the studyis to discuss the role of scouting as an effective tool in shaping the character of the younger generation. The results of active involvement in the scout movement are youngpeoplewhoareindependent,brave,religious,leaders,andresponsible.Thisarticleprovides anin-depthinsightintohowscoutingcanbeaneffectivemediuminshapingthecharacterof the younger generation, providing a solid foundation for personal improvement and positive contributionto society.
Why mega-earthquakes appear in flat landscapes?

Mega-quakes require the lifting of large earth crust. For slower decelerations of large mass, the stress generated has increasingly smaller vertical local component on the crust further to the east or to the northeast, such as off the pacific coast of Japan or east to Tibet. For faster accelerations of small mass such as the pacific plate off the coast of Americas, the closer crust has smaller local vertical component. When the stress across a large flat slope cancels out the weight of the crust simultaneously, mega-quakes occur.
Use of deep learning approaches for the prediction of diseases from medical images

Medical imaging is indispensable in the study or prediction of various medical conditions, early identification, surveillance, diagnosis, and therapy assessment. Understanding medical images for disease analysis using computer vision requires two key concepts: deep learning (DL) and artificial neural networks (ANNs). This chapter explains the DL approach (DLA), which uses medical picture analysis to determine if a disease is present or not. The creation of ANNs and a thorough examination of DLA, which have intriguing applications for medical imaging, will also be covered in this chapter. The majority of DLA implementations concentrate on digital histology, computed tomography, mammography, and X-ray pictures. It offers a thorough analysis of the articles for DLA-based classification, detection, and segmentation of medical images. This book chapter concludes by providing researchers, medical professionals, scientists, advanced students, and academics with valuable information to comprehend medical images and the significant role of ANNs and DLA, in predicting diseases.
Sonata for Violin and Piano “With the Questions” by Viktor Telychko as a Sample of the Master’s Metaphysical Biography

The purpose of the research is to conduct an art studies revision of the sonata for violin and piano “With the Questions” by Viktor Telychko, to confirm the idea of the opus appealing to philosophical categories similar to the demiurge’s world outlook and fostering his metaphysical biography constructing. The research methodology encompasses a range of the following approaches: analytical – to master an implementation of metaphysical questions in Viktor Telychko’s artwork; music studies – to grasp the content parameters of the presented masterpiece; hermeneutic – to interpret the senses introduced by the master; biographical – to study the originality of the chronicle and to analyse the composer’s individual history within the projection onto a creative pattern; systemic – to conduct a complex recognition of the issue of the study; theoretical generalisation – to summarise the research results. Scientific novelty. For the first time ever in national humanitarian studies, the sonata for violin and piano “With the Questions” by Viktor Telychko has been considered from the viewpoint of the artwork implementing the basic philosophical postulates; the following idea has been justified: the piece raises existential issues and demonstrates the master’s metaphysical chronicles. Conclusions. The postmodernism sonata has experienced considerable transformations related to reflecting personal and psychological concern. It is based on technical and style conceptions of the author’s original thinking, promotes important ideological positions of the master. In the 21st century, the genre reflects the master’s mentality and spiritual fundamentals professed by them, transfers to the sphere of philosophical objectification being represented by metaphysical biography. The latter is interpreted as the following: a symbolic depiction of ontological concepts of a personality’s life creativity reflected in an iconic civilizational artefact. The creative heritage of Viktor Telychko, a prominent profile in Ukrainian culture, is represented by a remarkable contribution where the sonata for violin and piano “With the Questions” stands out. Its consideration has revealed the seriousness and sense capacity of the presented conception. While developing the musical idea, the composer declares the following dominating metaphysical categories: birth, life, death, suffering, time, action, entity and some others. They are related to his existential aspirations (the artistic explication of their essence became the key task of various stages of being and was implemented via multifaceted elaborations), manifest the master’s essence and denote the metaphysical chronicle by Viktor Telychko.&#x0D; Keywords: metaphysical biography; the master’s life creativity; an artistic opus; creativity philosophy; Viktor Telychko; sonata for violin and piano “With the Questions”.
Fisionet: management system for phaysiotherapy clinic

The implementation of specialized systems in physiotherapy clinics plays a fundamental role in optimizing and improving the health services offered. With the continuous increase in demand for physiotherapy, effective clinical management is essential to ensure high-quality care. In this sense, this work aimed at the development of a system that aims to improve the efficiency of scheduling processes and management of physiotherapy clinics. The case study was used as a research methodology and Scrum as an agile method of software development. The system was developed in web technology with the JAVASCRIPT and PHP programming language. The results demonstrate that the developed system is capable of adding value to the clinic’s routine, making the management of scheduling processes more efficient and effective. Finally, it can be concluded that the system offers a robust and effective solution for managing patient scheduling processes, room control, financial control, and facilitates the visualization of scheduled and available times.
Phantom-Powered Nested Sampling

Abstract We introduce a novel technique within the Nested Sampling framework to enhance efficiency of the computation of Bayesian evidence, a critical component in scientific data analysis. In higher dimensions, Nested Sampling relies on Markov Chain-based likelihood-constrained prior samplers, which generate numerous 'phantom points' during parameter space exploration. These points are too auto-correlated to be used in the standard Nested Sampling scheme and so are conventionally discarded, leading to waste. Our approach discovers a way to integrate these phantom points into the evidence calculation, thereby improving the efficiency of Nested Sampling without sacrificing accuracy. This is achieved by ensuring the points within the live set remain asymptotically i.i.d. uniformly distributed, allowing these points to contribute meaningfully to the final evidence estimation. We apply our method on several models, demonstrating substantial enhancements in sampling efficiency, that scales well in high-dimension. Our findings suggest that this approach can reduce the number of required likelihood evaluations by at least a factor of 5. This advancement holds considerable promise for improving the robustness and speed of statistical analyses over a wide range of fields, from astrophysics and cosmology to climate modelling.
Does Economic Literacy Affect Inflation Expectations? An Experimental Survey Approach

This study investigates the effectiveness of the information treatment in the inflation expectations on individuals with varying levels of economic literacy. In this regard, we conducted an experimental survey that provided participants with information related to inflation and other macroeconomic variables. The study reveals that the information treatment was effective in assisting the participants revise their expectations closer to actual inflation. Notably, this was especially effective for those without an economics background as they revised it to align with the actual inflation. Additionally, we found that formal economics learning is insignificant in the formation of inflation expectations given that the relevant information is accessible. Results of the study shed light on the importance of addressing information friction, focusing on financial education and effective communication from central banks.&#x0D;
Person re-identification based on spectral nonlocal block and multiscale attention pyramid

Due to the complexity of the person re-identification scene, it is easy to be affected by visual changes such as illumination, occlusion, posture, etc, which makes the extracted person features will be insufficient and feature discrimination is poor, which in turn will lead to low retrieval accuracy. To address the above problems, a multi-scale attention pyramid network (SOAPNet) based on non-local block guidance of the spectral is proposed. First, the atlas non-local blocks are introduced into ResNet50 to capture remote dependencies more robustly and flexibly, so as to realize a wider range of information perception in the feature extraction stage; then, the multi-scale attention pyramid network is introduced into ResNet50, so that the model can focus more on the most critical and discriminative information in the person images, and this multi-scale attention strategy effectively solves the problem of The problem of insufficient features and poor discrimination in the person re-identification task, which enables the model to better distinguish person with different identities and extract more robust features. Experiments on Market1501, MSMT17, and DukeReID show that Rank1 is improved by 0.7%, 0.9%, and 1.2%, respectively, and mAP is improved by 0.5%, 1.0%, and 1.4%, respectively. The proposed method can significantly solve the above problems.
Research on SSD for the small target detection method based on deep supervision

SSD is a single-stage target detection model that uses different scales feature maps to make predictions. However, due to the insufficient nonlinearity of shallow feature maps and the lack of semantic information, the detection effect of small targets is much lower than that of medium and large targets. To address this issue, this paper proposes a strategy of deep supervision and feature fusion method based on the idea of a feature pyramid network on the basis of the SSD. Through a deep supervision strategy, the same supervisory signal is applied to multiple scales of features before fusion, narrowing the semantic gap between different scale features and improving the representation ability of multi-scale features for better fusion. The top-down fusion of features extracted from the SSD backbone network is used to improve the problem of lack of semantic information in shallow feature maps. The experimental results on the NWPUVHR-10 remote sensing dataset show that the average detection accuracy for small target detection is 88.3%, higher than the average detection accuracy of DSSD (78.7%), FSSD (86.7%), and SSD (84.2%).
Morse code detection and recognition algorithm based on YOLO-SVTR

Aiming at the problem of continuous detection and recognition of Morse codes in shortwave frequency band under time-frequency domain analysis, this paper proposes a YOLO-SVTR algorithm based on deep learning. Firstly, the short-time Fourier transform is used to transform the signal to be detected into a time-frequency image. Then, the lightweight improved YOLOv5 s model is used to detect Morse codes in the time-frequency image and automatically crop the target area. Finally, the cropped image is input into the SVTR-LCNet model to decode the corresponding text information. The simulation results show that the YOLO-SVTR algorithm effectively completes the integrated detection and recognition of Morse codes in the simulated short-wave band, and has good processing speed and high decoding accuracy.
Knowledge distillation with attention mechanism for anomaly detection

In the industrial domain, accurate detection and localization of abnormal images are crucial factors for ensuring production efficiency and quality. In recent years, methods in the field of unsupervised anomaly detection have predominantly centered around knowledge distillation models with a teacher-student structure. Although the application of knowledge distillation has significantly improved the precise identification of abnormal regions compared to traditional methods, the currently best-performing knowledge distillation models exhibit identical architectures for both the teacher and student networks. This limitation hampers the effective lightweighting of the student network and poses challenges in distinguishing between background and target objects in certain data with backgrounds, thereby affecting accuracy and wasting computational resources. To address this issue, we propose an innovative approach that integrates knowledge distillation with attention mechanisms for identifying abnormal regions in industrial anomaly images. Our method comprises two key features: firstly, transferring knowledge from a pretrained teacher network to a student network to enhance performance; secondly, incorporating attention mechanisms to direct the model’s focus towards potential abnormal regions, thereby enhancing detection accuracy. Our approach innovatively combines knowledge distillation with attention mechanisms, offering a novel solution for industrial anomaly image recognition. Through experimental validation, our method demonstrates superior performance compared to the original models, providing fresh insights for the field of industrial anomaly image analysis.
Optimization of hyperledger fabric consensus mechanism based on node behaviour

In response to the problem of security risks in the endorsement service phase of the consortium blockchain Hyperledger Fabric, the paper proposes an optimization scheme for the consensus mechanism based on the behaviour of endorsingnodes. By adding a behaviour monitoring module to the consortium blockchain architecture, the scheme records andanalyses the behaviour of each endorsing node in each transaction. In the monitoring module, a node capabilityvalueattribute is added to each node to reflect its operation status, and the normal operation of the endorsing node is judgedaccording to the capability value. The public key of the node and the hash value of the read-write set in the endorsement result are selected as the output information and passed to the monitoring module, so that the external module canobtainthe node behaviour information while ensuring that the business data on the blockchain is not leaked. Nodes withpoorendorsement performance will eventually be identified as malicious nodes due to their low capability value andbedeprived of endorsement rights. The experimental results show that this solution can timely and accurately detect andclean up the malicious nodes in the system that prevent transactions from reaching consensus, and ensure the normal execution of subsequent transactions.
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review : Single Anonymous • Conference submission management system : Indico • Number of submissions received : 89 • Number of submissions sent for review : 72 • Number of submissions accepted : 62 • Acceptance Rate (Submissions Accepted / Submissions Received × 100) : 69.7 • Average number of reviews per paper : 2 • Total number of reviewers involved : 44 • Contact person for queries : Name : Hirpa G. Lemu Email : hirpa.g.lemu@uis.no Affiliation : University of Stavanger, N-4036 Stavanger, Norway
Peer Review Statement

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing. • Type of peer review: Double Anonymous • Conference submission management system: Morressier • Number of submissions received: 57 • Number of submissions sent for review: 55 • Number of submissions accepted: 43 • Acceptance Rate (Submissions Accepted / Submissions Received × 100): 75.4 • Average number of reviews per paper: 3 • Total number of reviewers involved: 12 • Contact person for queries: Name: Dina Wahyu Trisnawati Email: dina.trisnawati@fp.umy.ac.id Affiliation: Universitas Muhammadiyah Yogyakarta
Domain phishing: staying a step ahead of the threats

Domain hijacking and cybersquatting have become popular techniques among threat actors, especially those engaged in phishing. Organisations need to pay attention to domain security – to protect themselves and their partners and customers. Fortunately, there are tools organisations can use to keep their domains, and their brands, safe.