Reviewerly/exHarmony huggingface dataset:
Modernization of the educational potential under the conditions of partial military mobilization in Russia

The specific problems of the development of the educational potential of Russians related to the sharp aggravation of the military confrontation in the world, the intensification of hostilities in the Ukraine, the implementation of partial mobilization, as well as the mobilization of educational training of part of the economically active population of Russia are clarified. Theoretical developments devoted to the study of educational potential are analyzed, and these concepts are conditionally ranked into interdisciplinary, general sociological and military-sociological ones. The integration of different views made it possible to substantiate the need to clarify the trend in the development of the educational potential of the population as a set of knowledge, skills, abilities, culture and practical experience of individuals in the areas of both general and partially military-professional action. The hypothesis is put forward according to which the modernization of the educational potential of the population under the conditions of partial military mobilization in Russia involves: updating its content (introduction of additional military educational components); saturation of scientific and spiritual quality (accumulation of the innovative component of the abilities of its carriers); allocation of adaptive potential as an independent component of self-development (accumulation of the adaptive component of the abilities of carriers of educational potential). The ways of modernization of the educational potential of Russians are presented. The first one is the transition to a comprehensive and continuous formation of educational potential. At all levels of general, professional, and additional education, there should be a dual target orientation: general and special civil; general military. The second one is the formation of a proactive (proactive) type of formation of educational potential. In the education system it is important: to transform the nature of scientific and investment flows; to activate the channels of socio-cultural mobility; to reverse the saturation of civilian and military human capital of trainees and trainees. The third one is the allocation of adaptive potential as a separate component of educational potential. It is proved that under the new conditions, the realization of educational potential depends on the ability of individuals to quickly assess changes in the external social environment, adapt, form new models of influence in the process of work, service, military influence on the enemy. Adaptive educational potential is proposed to be considered as a characteristic of an individual's educational abilities to adapt their own activities in both peacetime and wartime.
University Classes: Humanitarian Aspect – “Sweet Dream” and Reality in the Daily Activities of Higher School Teachers

The article discusses the author’s forms and methods of work in the course of teaching disciplines of the hu-manities cycle, aimed at activating students in cognition of the studied material, developing their skills in con-ducting scientific discussion. Methodologically, the study is based on empirical work, which involved general scientific methods and techniques (observation, analysis, generalization), as well as special (heuristic, reverse link method, survey, peer-to-peer dialogue). The aim of the study is to represent the general idea of selecting an intensive direction of conducting classes due to the strict time limit. To achieve it a number of tasks were accomplished, including: definition of modern role functionality for teacher and student, characterization of the educational process from the point of view of its restructuring in the direction of cognitive activity activation of students through the introduction of innovative forms and methods of work, identification of key points of the author's methodology of lecture and seminar classes, effectively tested in Kuban universities, recommenda-tions formulation. Conclusion dwells upon the fact that the position of a teacher in higher education should be active, then the solution to the task of improving the quality of education will become real.
Expansion of Screen Technologies in Culture as a Condition of Semantic and Value Devastation

The article examines a number of new views on the features of the mass expansion processes of screen tech-nologies in the space of modern culture, creating conditions for its stable semantic, value, teleological depreci-ation (nihitogenesis), and especially emphasizes the permanent influence of this expansion on the perception and consciousness of the screen device user. Based on the concept of historical development of the nihilistic tendencies in the European cultural tradition, its historically established features, the author in the study pays particular attention to the analysis of the attempts to revise the achieved level of cultural development and re-jection of its achievements in order to restart from the zero level of the general process of cultural genesis as part of the technological screen expansion. According to the results of the study, the causes and conditions for the transformation of pre-existing forms of nihilistic negation into existing trends of meaningful devastation and semantic devastation of culture are identified and analyzed.
Analisis Modifikasi Desain pada Lokomotif CC-201 Tipe GE U18C dengan Metode Simulasi CFD

The CC-201-type U18C locomotives are widely used for public transportation in Indonesia. Like other modes of transportation or vehicles, the body's design is an important factor to consider because it influences the aerodynamic capabilities of the vehicle. The study aims to analyze the effect of variations in the design angle of the CC-201 type U18C locomotive body on the coefficient of drag and aerodynamics. The method used in this research is CFD simulation using CAE-based engineering software, Ansys Fluent R2 2022. CFD simulations were performed on locomotive body designs with angle variations of 90°, 135°, and 150° using the same boundary condition parameters. The results show that the locomotive body design with the 60° variation has the smallest drag coefficient value of 0.51076379. The study conclusion explains that changing the angle of 150 degrees at the top of the GE U18C-type locomotive body has a significant effect on lowering the value of the drag coefficient by up to 29%.
Application of Polya Strategy Assisted by Concrete Media to Improve Numeracy and Learning Outcomes in Elementary School Students

The background of this research is the low numeracy skills of students in solving problem-solving questions, the less attractive learning media used by the teacher and in the learning process, and the teacher's need to use the appropriate model/strategy in the learning process. This study aims to describe the implementation of the Polya Strategy assisted by concrete media to improve numeracy and student learning outcomes. Classroom Action Research (PTK) uses a model developed by Ernest T. Stranger, carried out during II actions. Each action has 3 stages, namely Look, Think, and Act. Researchers researched fifth-grade students at SD Pangudi Luhur Ambarawa with 37 students. This study's data collection techniques included interviews, observation, evaluation tests and documentation. The enumeration results of class V students at SD Pangudi Luhur Ambarawa in action I with a class average value of 70%, while action II achieved a class average of 86%. The learning outcomes of students in Action I with a class average value of 68%, while in Action II achieved a class average value of 80%.
BiPaSs: Further Investigation of Fast Pathfinding in Wikidata

Purpose: A previous paper proposed a bidirectional A* search algorithm for quickly finding meaningful paths in Wikidata that leverages semantic distances between entities as part of the search heuristics. However, the work lacks an optimization of the algorithm’s hyperparameters and an evaluation on a large dataset among others. The purpose of the present paper is to address these open points. Methodology: Approaches aimed at enhancing the accuracy of the semantic distances are discussed. Furthermore, different options for constructing a dataset of dual-entity queries for pathfinding in Wikidata are explored. 20% of the compiled dataset are utilized to fine-tune the algorithm’s hyperparameters using the Simple optimizer. The optimized configuration is subsequently evaluated against alternative configurations, including a baseline, using the remaining 80% of the dataset. Findings: The additional consideration of entity descriptions increases the accuracy of the semantic distances. A dual-entity query dataset with 1,196 entity pairs is derived from the TREC 2007 Million Query Track dataset. The optimization yields the values 0.699/0.109/0.823 for the hyperparameters. This configuration achieves a higher coverage of the test set (79.2%) with few entity visits (24.7 on average) and moderate path lengths (4.4 on average). For reproducibility, the implementation called BiPaSs, the query dataset, and the benchmark results are provided. Value: Web search engines reliably generate knowledge panels with summarizing information only in response to queries mentioning a single entity. This paper shows that quickly finding paths between unseen entities in Wikidata is feasible. Based on these paths, knowledge panels for dual-entity queries can be generated that provide an explanation of the mentioned entities’ relationship, potentially satisfying the users’ information need.
AN IDEAL LEGAL TENDER FOR THE DIGITAL ERA

The Covid-19 pandemic has accelerated a shift towards digital payments and altered consumer behaviour when it comes to making payments. As a result, the use of state-issued money as legal tender continues to decline in most countries. In turn, the functions and existence of legal tender has decreased. Acknowledging such facts, the purpose of this research is to examine an ideal legal tender for the digital era that can restore the legal tender function while accommodating payment innovation. This research explores legal theories on money and legal tender, as well as the characteristics of various forms of money issued by the State and the private sector, i.e., fiat money, commercial bank money, cryptocurrency, and central bank digital currency. This research concludes that an ideal legal tender for the digital era should incorporate both cash and digital currency. Under this notion, central bank digital currency might serve as the ideal legal tender for the digital era. Nonetheless, there are certain prerequisites to the issuance of such legal tender. These include at least conducting thorough interdisciplinary research and pilot projects by the central bank, establishing an adequate regulatory framework, and ensuring public acceptance of such currency as a means of payment, as well as developing the necessary infrastructure.
Examining +2 Level Students' Email Writing Proficiency: A Critical Analysis and Recommendations

This paper examines +2 level students’ email writing proficiency critically and recommends the necessary tips for improvements. Email writing has become a crucial aspect of teaching and learning activities in EFL classes. It is the quickest means of communication for bulk messaging. The practice of post offices is almost obsolete. The postman used to deliver letters to people from one place to another place and the delay was common. Now, in the digital age, email writing has become the fastest means of communication for disseminating the messages to the recipients. Despite this, both the teachers and students do not take the email writing process as a crucial matter. The findings of the study show that +2 level students write emails like a letter in their exam papers. They can do the same in reality as well. Their teachers should instruct them properly. Email writing is not as simple as the teachers and students think. Email writing does not only inform, it also persuades the recipients. The study aims at empowering the +2 level students’ email writing proficiency by suggesting with required methods, techniques and tips. Their skills are not well patterned because their teachers do not instruct them sincerely. Therefore, both the teachers and students should tackle this email writing with the exact formats and methods. The study is qualitative research and it adopts the descriptive survey methods for the analysis of their email writing skills.
A shadow preservation framework for effective content-aware image retargeting process

&lt;p&gt;In the discipline of image retargeting, the structure of shadows in the image is required to be preserved since it gives structural information about the objects. Many traditional image retargeting techniques do not pay attention to preserve the shadow objects present in the image. In this paper a shadow-preservation framework is proposed in which the saliency map is derived using segmentation-based gPb-owt-ucm approach to emphasize the salient regions. To assess the quality of saliency map a fixation prediction analysis is conducted on each section of the image using the eye tracker technology. Second, to pay more attention on the shadow objects a shadow map is developed after executing image pre-processing, shadow detection, region growing, and region filling operations. To rectify the issue of misclassification of shadow pixels erosion and dilation operations are performed. To obtain an efficient importance map, a gradient map is prepared using canny operator which is further combined with the saliency map and shadow map. The obtained importance map is supplied to the seam diversion based image retargeting (SDIR) technique to resize the image in horizontal and vertical directions. To justify the efficiency of the proposed framework’s the obtained results are compared with the existing state-of-the-art. By preserving shadows, the proposed framework enhances the overall visual quality and maintains the integrity of objects in the retargeted images. The framework’s effectiveness is validated through quantitative evaluations and visual comparisons with existing methods. The results demonstrate its potential for improving content-aware image retargeting applications, paving the way for more realistic and visually appealing image resizing techniques in various domains.&lt;em&gt;&lt;/em&gt;&lt;/p&gt;
Drone Powered by Solar Energy and Whale Optimization Algorithm

In this paper, the whale optimization algorithm (WOA), a potent swarm intelligence technique that has been widely applied in numerous sectors, including the parameter identification of solar cells and PV modules, is discussed in this work. A unique modified WOA (MWOA) that introduces both a mutation method based on Levy flight and a local search mechanism of pattern search to better balance the exploration and exploitation of WOA. On the one hand, Levy flight can force the algorithm to abandon the local optimum and avoid stagnation; as a result, it can stop the algorithm from losing diversity and improve the algorithm's ability to conduct global searches. However, pattern search, a direct search technique, has a high convergence rate and good stability, which can increase local search efficiency. Therefore, the ability of WOA to find the optimal solution can be significantly increased by combining these two techniques. Additionally, MWOA may be used to determine the unknown parameters of two different types of PV modules under various light irradiance and temperature circumstances, as well as to estimate parameters in the single diode model (SDM), double diode model (DDM), and PV modules.
Knowledge Graph Based Recommender for Automatic Playlist Continuation

In this work, we present a state-of-the-art solution for automatic playlist continuation through a knowledge graph-based recommender system. By integrating representational learning with graph neural networks and fusing multiple data streams, the system effectively models user behavior, leading to accurate and personalized recommendations. We provide a systematic and thorough comparison of our results with existing solutions and approaches, demonstrating the remarkable potential of graph-based representation in improving recommender systems. Our experiments reveal substantial enhancements over existing approaches, further validating the efficacy of this novel approach. Additionally, through comprehensive evaluation, we highlight the robustness of our solution in handling dynamic user interactions and streaming data scenarios, showcasing its practical viability and promising prospects for next-generation recommender systems.
A NOVEL CARDIAC IMAGE SEGMENTATION METHOD USING AN OPTIMIZED 3D U-NET MODEL

Medical image segmentation holds significant importance for doctors, patients, and the entire health care industry. For doctors, it provides more accurate information about cardiac structures, aiding in improving diagnoses and treatment decisions. For patients, segmentation techniques enable personalized medical care, enhancing treatment outcomes and satisfaction. The entire health care sector benefits from the advancement of this technology, driving the development of medical science and contributing to better health care quality and patient well-being. Additionally, segmentation plays a crucial role in research and education, facilitating the accumulation and dissemination of medical knowledge. In summary, the application of medical image segmentation has profound implications for progress in the medical field and patient welfare. In recent years, with technological advancements and innovative algorithms, medical image quality has greatly improved, with higher resolution and reduced noise and artifacts. Simultaneously, the application of deep learning techniques has made the automatic analysis and diagnosis of medical images more precise and efficient. However, due to the complex structures and diversity often present in medical images, models tend to have limited generalization across different datasets, leading to unstable segmentation performance. Considering the excellent image segmentation performance of the three-dimensional (3D) U-Net model, this study introduces an improved spatial attention mechanism on the basis of the 3D U-Net model to enhance its segmentation performance. The spatial attention mechanism enhances the model’s feature extraction capabilities. The enhanced network can capture dependencies among features across both channel and spatial dimensions in the entire global scope. Additionally, it can strengthen any two correlated features within the input feature vector, thereby enhancing the model’s representational capacity. Through detailed experimental validation, the effectiveness of the proposed model is thoroughly demonstrated. Its superiority in performance and computational efficiency positions it as a significant breakthrough in the medical image segmentation field, providing a strong foundation for future research and clinical practice in medical image processing.
Approaches of Higher Vocational Education Method Based on Machine Vision Technology

With the continuous development and improvement of vocational education, more and more higher vocational education institutions are beginning to explore the integration of machine vision technology into teaching. The goal is to improve the effectiveness and quality of teaching, including intelligent
Design of Online Evaluation System for Blended Teaching in Vocational Education

Blended teaching of vocational education includes online and offline teaching. Using online means to evaluate students' academic performance has the advantages of real-time and efficiency. Aiming at the online evaluation module, this paper divides the course performance index, most of the structure,
Classification of All t-Resilient Boolean Functions with t + 4 Variables

We apply Siegenthaler’s construction, along with several techniques, to classify all (n−4)-resilient Boolean functions with n variables, for all values of n ≥ 4, up to the extended variable-permutation equivalence. We show that, up to this equivalence, there are only 761 functions for any n larger than or equal to 10, and for smaller values of n, i.e., for n increasing from 4 to 9, there are 58, 256, 578, 720, 754, and 760 functions, respectively. Furthermore, we classify all 1-resilient 6-variable Boolean functions and show that there are 1 035 596 784 such functions up to the extended variable-permutation equivalence.
Pengembangan Media Pembelajaran Berbasis Aplikasi Android Menggunakan Power Point Dan I-Spring Pada Materi Garis Dan Sudut Untuk Siswa SMP Kelas VII

This research aims to produce products in the form of learning media based on android applications using Powerpoint and I-Spring on line and angle materials for junior high school students in grade VII that are valid, practical and effective. The method used in this study is the Research and Development (R&amp;D) method with the ADDIE development model consisting of 5 stages, namely analysis, design, development, implementation and evaluation. Data collection techniques and instruments used were interviews, questionnaires and tests. The data analysis technique used is quantitative and qualitative analysis techniques. The results showed that the learning media based on the android application that was developed met the valid, practical and effective eligibility criteria. The results of the media eligibility were obtained from the assessment of material experts with an average of 4.4 and media expert assessments of 4.4 so that they were categorized as "valid", the results of the student evaluation tests obtained a passing presentation of 78.6% which was included in the "Effective" category, while the average response to the use of subject teachers is 3.4, and the student response to this learning media is 3.48 so it is included in the "practical" category.
An improved color consistency optimization method based on the reference image contaminated by clouds

Optimizing color consistency across multiple images is a crucial step in creating accurate digital orthophoto maps (DOMs). However, current color balance methods that rely on a reference image are susceptible to cloud and cloud shadow interference, making it challenging to ensure color fidelity and a uniform color transition between images. To address these issues, an improved method for color consistency optimization has been proposed to enhance image quality using optimized low-resolution reference images. Initially, the original image is utilized to reconstruct areas affected by clouds or cloud shadows on the reference image. For seamless cloning, a Poisson blending algorithm is employed to minimize color differences between reconstructed and other regions. Subsequently, based on a weighting approach, the high-frequency information obtained through Gaussian and bilateral filtering is superimposed to smooth the image boundary and ensure color continuity between images. Finally, local linear models are constructed to correct image color based on the optimized reference and down-sampled images. To validate the robustness of this approach, we tested it on two challenging datasets covering a wide area. Compared to state-of-the-art methods, our approach offers significant advantages in both quantitative indicators and visual quality.