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Item Russian Publications in Web of Science: A Bibliometric Study(2023) Fiala, Dalibor; Maltseva, DariaThis article presents a bibliometric study of 1.38 million Russian publications indexed in Web of Science as of May 2022 without any restrictions as to document types, time periods, scientific disciplines, etc. From this perspective, the present analysis reflects Russian research’s true presence and visibility in the most prestigious scientific literature database. The main results obtained are: a) There was a rapid increase in research production in the 2010s, but the share of the Russian output in the global research production is still below 3%. b) International collaborative publications account for about 30% of Russian papers but around 70% of Russian citations. c) Physics, chemistry, and engineering are the most productive Russian research areas, but their citation impact is below the world average in those respective fields. d) The most frequently collaborating countries are the United States, Germany, and France, but Canada and Switzerland consistently contribute to the greatest relative citation impact of collaborative papers in the top ten research areas.
Item Analysis of Cited References in Russian Publications on Web of Science(2024) Fiala, Dalibor; Maltseva, DariaIn this article we analyze the cited references in 1.38 million papers by Russian (co-)authors indexed in the Web of Science database until May 2022. Similarly, to the established processes in the so-called Reference Publication Year Spectroscopy (RPYS), we study the distribution of the references across the cited years and seek to identify the peak years with the publications that attracted the most attention of Russian scholars. In this way, the historical roots of Russian science may be traced and we take a closer look at these most influential works. In addition, we investigate the evolution of the mean age of references and of their average number per paper over time and inspect the most frequently cited sources. The results show that the average number of references in Russian papers has been steadily increasing, but the mean age of references has been declining in the most recent years. Also, the foundations of Russian science seem to be physics of particles and electrochemistry and have recently become based more internationally than in the past. This study is the first of its kind and may help better understand the character of Russian research.Item Editing mesh sequences with varying connectivity(2024) Hácha, Filip; Dvořák, Jan; Káčereková, Zuzana; Váša, LiborTime-varying connectivity of triangle mesh sequences leads to substantial difficulties in their processing. Unlike editing sequences with constant connectivity, editing sequences with varying connectivity requires addressing the problem of temporal correspondence between the frames of the sequence. We present a method for time-consistent editing of triangle mesh sequences with varying connectivity using sparse temporal correspondence, which can be obtained using existing methods. Our method includes a deformation model based on the usage of the sparse temporal correspondence, which is suitable for the temporal propagation of user-specified deformations of the edited surface with respect to the shape and true topology of the surface while preserving the individual connectivity of each frame. Since there is no other method capable of comparable types of editing on time-varying meshes, we compare our method and the proposed deformation model with a baseline approach and demonstrate the benefits of our framework.
Item Accelerated multi-hillshade hierarchic clustering for automatic lineament extraction(2024) Kaas, Ondřej; Šilhavý, Jakub; Kolingerová, Ivana; Čada, VáclavThe lineaments are linear features reflecting mountain ridges or discontinuities in the geological structure. Recently, an automatic approach of their recognition based on multi-hillshade hierarchic clustering (MHHC) has been developed, based on line extraction from a raster image. This paper presents a modification of MHHC, which solves the spatial line segment clustering as a facility location problem. The proposed modification is faster than MHHC while not changing the method’s core.Item Improved Methodology for Assessment of Communication Protocols for Distributed Road Traffic Simulation(2024) Potužák, TomášThis paper describes an improved methodology for testing and assessment of high-level communication protocols for micro-scale (or microscopic) distributed road traffic simulations. The methodology investigates the dependencies of the communication protocols’ performance on various features of the simulation and enables to easily calculate score for each of the tested protocols. Using the scores, the tested protocols can be directly compared. The improved version of the methodology is an evolution of its original version. It newly incorporates the assessment of the error introduced into the simulation by lossy communication protocols and reduces overall number of performed tests.Item Simplification of contour lines, based on axial splines, with high-quality results(2023) Bayer, Tomáš; Kolingerová, Ivana; Čelonk, Marek; Lysák, JakubThis paper introduces a new simplification method providing high-quality contour lines derived from the 3D point cloud. It combines the simplification potential and the splines with the generalized axial symmetry. It applies to large-scale maps (1:5000–1:25,000). It significantly improves all geometric and shape parameters of contour lines, namely in flatter areas. The simplified contour lines preserve the given vertical error, lie within the vertical buffer, are aesthetically pleasing, and have similar spacing; their artificial oscillations are significantly reduced.Item An incremental facility location clustering with a new hybrid constrained pseudometric(2023) Bayer, Tomáš; Kolingerová, Ivana; Potůčková, Markéta; Čábelka, Miroslav; Štefanová, EvaThe Euclidean metric, one of the classical similarity measures applied in clustering algorithms, has drawbacks when applied to spatial clustering. The resulting clusters are spherical and similarly sized, and the edges of objects are considerably smoothed. This paper proposes a novel hybrid constrained pseudometric formed by the linear combination of the Euclidean metric and a pseudometric plus penalty. The pseudometric is used in a new deterministic incremental heuristic facility location algorithm (IHFL). Our method generates larger, isotropic, and partially overlapping clusters of different sizes and spatial densities, better adapting to the surface complexity than the classical non-deterministic clustering. Cluster properties are used to derive new features for supervised/unsupervised learning. Possible applications are the classification of point clouds, their simplification, detection, filtering, and extraction of different structural patterns or sampled objects. Experiments were run on point clouds derived from laser scanning and images.Item Model-Free-Communication Federated Learning: Framework and application to Precision Medicine(2024) De Falco, Ivan; Della Cioppa, Antonio; Koutný, Tomáš; Scafuri, Umberto; Tarantino, ErnestoThe problem of executing machine learning algorithms over data while complying with data privacy is highly relevant in many application areas, including medicine in general and Precision Medicine in particular. In this paper, an innovative framework for Federated Learning is proposed that allows performing machine learning and effectively tackling the issue of data privacy while taking a step towards security during communication. Unlike the standard federated approaches where models should travel on the communication networks and would be subject to possible cyberattacks, the models proposed by our framework do not need to travel, thus moving in the direction of security improvement. Another very appealing feature is that it can be used with any machine learning algorithm provided that, during the learning phase, the model updating does not depend on the input data. To show its effectiveness, the learning process is here accomplished by an Evolutionary Algorithm, namely Grammatical Evolution, thus also obtaining explicit knowledge that can be provided to the domain experts to justify the decisions made. As a test case, glucose values prediction for a number of patients with type 1 diabetes is considered and is tackled as a classification problem, the goal being to predict for any future value a possible range. Finally, a comparison of the performance of the proposed framework is performed against that of a non-Federated Learning approach.Item Cross-lingual aspect-based sentiment analysis: A survey on tasks, approaches, and challenges(2025) Šmíd, Jakub; Král, PavelAspect-based sentiment analysis (ABSA) is a fine-grained sentiment analysis task that focuses on understanding opinions at the aspect level, including sentiment towards specific aspect terms, categories, and opinions. While ABSA research has seen significant progress, much of the focus has been on monolingual settings. Cross-lingual ABSA, which aims to transfer knowledge from resource-rich languages (such as English) to low-resource languages, remains an under-explored area, with no systematic review of the field. This paper aims to fill that gap by providing a comprehensive survey of cross-lingual ABSA. We summarize key ABSA tasks, including aspect term extraction, aspect sentiment classification, and compound tasks involving multiple sentiment elements. Additionally, we review the datasets, modelling paradigms, and cross-lingual transfer methods used to solve these tasks. We also examine how existing work in monolingual and multilingual ABSA, as well as ABSA with LLMs, contributes to the development of cross-lingual ABSA. Finally, we highlight the main challenges and suggest directions for future research to advance cross-lingual ABSA systems.Item AhiLS - an Algorithm for Establishing Hierarchy among Detected Weak Local Reflection Symmetries in Raster Images(2024) Podgorolec, David; Kolingerová, Ivana; Lovenjak, Luka; Žalik, BorutA new algorithm is presented for detecting the local weak reflection symmetries in raster images. It uses contours extracted from the segmented image and a convex hull. A tree representing the hierarchy of the detected local symmetries is the result of the algorithm.Item A case study on entropy-aware block-based linear transforms for lossless image compression(2024) Žalik, Borut; Podgorolec, David; Kolingerová, Ivana; Strnad, Damjan; Kohek, ŠtefanData compression algorithms tend to reduce information entropy, which is crucial, especially in the case of images, as they are data intensive. In this regard, lossless image data compression is especially challenging. Many popular lossless compression methods incorporate predictions and various types of pixel transformations, in order to reduce the information entropy of an image. In this paper, a block optimisation programming framework is introduced to support various experiments on raster images, divided into blocks of pixels. Eleven methods were implemented, including prediction methods, string transformation methods, and inverse distance weighting, as a representative of interpolation methods.Item A New Transformation Technique for Reducing Information Entropy: A Case Study on Greyscale Raster Images(2023) Žalik, Borut; Strnad, Damjan; Podgorolec, David; Kolingerová, Ivana; Lukač, Luka; Lukač, Niko; Kolmanič, Simon; Žalik, Krista Rizman; Kohek, ŠtefanThis paper proposes a new string transformation technique called Move with Interleaving (MwI). Four possible ways of rearranging 2D raster images into 1D sequences of values are applied, including scan-line, left-right, strip-based, and Hilbert arrangements.Item A Novel Radial Basis Function Description of a Smooth Implicit Surface for Musculoskeletal Modelling(2024) Červenka, Martin; Kohout, Josef; Lipus, BogdanAs musculoskeletal illnesses continue to increase, practical computerised muscle modelling is crucial. This paper addresses this concern by proposing a mathematical model for a dynamic 3D geometrical surface representation of muscles using a Radial Basis Function (RBF) approximation technique. The objective is to obtain a smoother surface while minimising data use, contrasting it from classical polygonal (e.g. triangular) surface mesh models or volumetric (e.g. tetrahedral) mesh models. The paper uses RBF implicit surface description to describe static surface generation and dynamic surface deformations based on its spatial curvature preservation during the deformation. The novel method is tested on multiple data sets, and the experiments show promising results according to the introduced metrics.Item Algorithm for detecting cyclone and anticyclone centres from mean sea level pressure layer(2023) Prantl, Martin; Žák, Michal; Prantl, DavidAutomatic methods for identifying and tracking pressure systems have been traditionally focused on cyclones (and particularly on tropical cyclones), but the question of anticyclone centre detection remained unsolved since they are usually not a source of turbulent weather, precipitation, etc. An algorithm for automatic detection of both, cyclones and anticyclones based on the mean sea-level pres-sure field, is presented. The main advantages of our solution are easy implementation based on two-dimensional raster data, suffi-cient performance of the algorithm, and especially the possibility of high-pressure systems detection. Moreover, the presented solution does not need direct terrain filteringItem Efficient Speed-Up of the Smallest Enclosing Circle Algorithm(2022) Šmolík, Michal; Skala, VáclavThe smallest enclosing circle is a well-known problem. In this paper, we propose modifications to speed-up the existing Weltzl’s algorithm. We perform the preprocessing to reduce as many input points as possible. The reduction step has lower computational complexity than the Weltzl’s algorithm and thus speed-ups its computation. Next, we propose some changes to Weltzl’s algorithm. In the end are summarized results, that show the speed-up for 10^6 input points up to 100 times compared to the original Weltzl’s algorithm. Even more, the proposed algorithm is capable to process significantly larger data sets than the standard Weltzl’s algorithm.Item Сравнительный анализ возможностей WoS и eLibrary для анализа библиографических сетей(2024) Maltseva, Daria; Pavlova, Irina; Kapustina, Lika; Vashchenko, Vasilisa; Fiala, DaliborВ статье проводится сравнительный анализ баз данных научных публикаций Web of Science Core Collection и eLibrary с целью выделения их особенностей и описания возможностей анализа при изучении библиографических сетей российских авторов. Актуальность исследования определяется необходимостью адаптации и разработки подходов и инструментов для сбора, предобработки и анализа библиографических данных на русском языке. Анализ проводится на основе сравнения массивов данных публикаций в научных журналах в области социологии, выгруженных за период 2010–2021 гг. Выделяются основания для сопоставления двух баз, характеризующие получение доступа к данным, организацию данных в базах, количественные и содержательные характеристики данных. Анализ отобранных параметров позволяет найти пересечения между массивами данных и содержательными результатами анализа. Делаются выводы о соотношении двух баз, их возможностях и ограничениях по использованию в качестве основного (единственного) источника информации, даются рекомендации об их использовании для изучения отечественной науки.Item Kinetic, equilibrium, and thermodynamic studies of adsorptive interactions of eosin-B on chemically treated orange peels(2024) Anwar, Mamoona; Mahmood, Tahir; Pawlicka, Agnieszka; Thang, Nguyen Hoc; Mouček, Roman; Alharbi, Sulaiman Ali; Alfarraj, SalehThe present study investigated the adsorption of eosin B on the surface of powdered and chemically treated orange peels, along with this process's condition optimizations, kinetics, and thermodynamics. The adsorbent dose (0.1–0.5 g), temperature (298, 303, 308, and 313 K), contact time (15–120 min), initial pH value (2–11) of the solution, and interfering salts (0.01 and 0.1 mol L−1) were all taken into consideration during the experiments. At all investigated temperatures and pH of 2, adsorption was more favourable. Although the Langmuir model might also represent the adsorption data, the Freundlich and Dubinin–Radushkevich (D–R) models provided a good description. The pseudo-second order kinetic model was followed during the adsorption process. The mechanics of the rate-controlling step were examined by applying the intra-particle diffusion-based mass transfer model to the experimental data. It was discovered that the only process that controlled the rate was intra-particle diffusion. The adsorption process appears to be spontaneous, and endothermic and involves van der Waals forces based on thermodynamic data.Item Měření mozkové aktivity v profesionálním tanečním prostředí – studie(2024) Roth Elblová, Markéta; Mouček, RomanPropojení těla a mysli a jejich vzájemná konjunkce jsou stále aktuálnějším, mnohooborovým tématem. Cíl: Cílem práce bylo zjistit, do jaké míry působí naše myšlenky v profesionálním tanečním prostředí na průběh mozkových frekvencí a jakým způsobem se propisují do našeho organizmu a pohybu. Metody: V rámci studie proběhlo měření mozkové činnosti nositelným EEG zařízením Muse a vizuální analýza pohybu z tanečního prostředí, prvku plié (flexe a extenze kolenních kloubů). Sledovanými a měřenými jedinci bylo 16 studentů Katedry tance, Hudební a taneční fakulty Akademie múzických umění v Praze. Sledovali jsme mozkové frekvence v mnoha fázích (situacích): bez konkrétní myšlenky (soustředění se) a bez pohybu, při konkrétní myšlence bez pohybu, pohyb bez konkrétní myšlenky, pohyb s konkrétní myšlenkou a na závěr opět myšlenku bez pohybu, která byla mimo obor a rámec výzkumu. Výsledky: U 14 účastníků experimentu jsme získali dostatečně kvalitní EEG signál k další analýze. U 12 účastníků byla prokázána změna v mozkových frekvencích odlišujících aktivity s nižší a vyšší vědomou koncentrací. Závěr: Výstup popisuje zjištění ohledně propojení myšlenek, těla a pohybu na základě měřitelných dat. EEG zařízení Muse je použitelné pro získávání EEG signálu dostatečné kvality v experimentech vyžadujících pohyb odehrávající se v reálných podmínkách. V získaném EEG signálu je možné detekovat změny v mozkové aktivitě účastníků při stavech uvolněné bdělosti a vědomé koncentrace. Vizuální analýza pohybu reflektuje, že syntéza specifické myšlenky a pohybu přispívá k eliminaci špatných pohybových návyků, které ruší nejen technickou čistotu provedení pohybového prvku, ale také optimální držení těla, koordinaci pohybu a jednotlivých anatomických struktur.Item A comparative study of cross-lingual sentiment analysis(2024) Přibáň, Pavel; Šmíd, Jakub; Steinberger, Josef; Mištera, AdamThis paper presents a detailed comparative study of the zero-shot cross-lingual sentiment analysis. Namely, we use modern multilingual Transformer-based models and linear transformations combined with CNN and LSTM neural networks. We evaluate their performance in Czech, French, and English. We aim to compare and assess the models’ ability to transfer knowledge across languages and discuss the trade-off between their performance and training/inference speed. We build strong monolingual baselines comparable with the current SotA approaches, achieving state-of-the-art results in Czech (96.0% accuracy) and French (97.6% accuracy). Next, we compare our results with the latest large language models (LLMs), i.e., Llama 2 and ChatGPT. We show that the large multilingual Transformer-based XLM-R model consistently outperforms all other cross-lingual approaches in zero-shot cross-lingual sentiment classification, surpassing them by at least 3%. Next, we show that the smaller Transformer-based models are comparable in performance to older but much faster methods with linear transformations. The best-performing model with linear transformation achieved an accuracy of 92.1% on the French dataset, compared to 90.3% received by the smaller XLM-R model. Notably, this performance is achieved with just approximately 0.01 of the training time required for the XLM-R model. It underscores the potential of linear transformations as a pragmatic alternative to resource-intensive and slower Transformer-based models in real-world applications. The LLMs achieved impressive results that are on par or better, at least by 1%–3%, but with additional hardware requirements and limitations. Overall, this study contributes to understanding cross-lingual sentiment analysis and provides valuable insights into the strengths and limitations of cross-lingual approaches for sentiment analysisItem Multispectral Image Generation from RGB Based on WSL Color Representation: Wavelength, Saturation, and Lightness(2023) Skala, VáclavImage processing techniques are based nearly exclusively on RGB (red–green–blue) representation, which is significantly influenced by technological issues. The RGB triplet represents a mixture of the wavelength, saturation, and lightness values of light. It leads to unexpected chromaticity artifacts in processing. Therefore, processing based on the wavelength, saturation, and lightness should be more resistant to the introduction of color artifacts. The proposed process of converting RGB values to corresponding wavelengths is not straightforward. In this contribution, a novel simple and accurate method for extracting the wavelength, saturation, and lightness of a color represented by an RGB triplet is described. The conversion relies on the known RGB values of the rainbow spectrum and accommodates variations in color saturation. © 2023 by the author.
