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32nd International Workshop on Vertex Detectors, VERTEX 2023

作者： Oblakowska-Mucha, Agnieszka Faculty of Physics and Applied Computer Science AGH University of Krakow Al. Mickiewicza 30 Krakow30-059 Poland

The primary focus of the LHC experiments was the observation of Standard Model particles and the search for unexplored signatures indicative of New physics. Given the current discoveries and measurements done so far, the detectors and the trigger architecture are being changed to allow for the searches of long-lived particles. LHCb's trackers have excelled in the precise reconstruction of heavy flavour hadrons, and the experiment is now at the forefront of designing flexible trigger systems. Similarly, ATLAS and CMS, with their precise trackers, are also exploring new avenues by implementing innovative triggers to search for long-lived particles. The techniques of the reconstruction of displaced tracks and vertices in the upgraded LHCb detector, complementary with other general-purpose detectors at the LHC, are presented in this proceedings. © Copyright owned by the author(s)

关键词： Hadrons

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Video classification for efficient data storage using deep learning: a comparison of sequential and simultaneous feature extraction methods

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Multimedia Tools and Applications 2025年第6期84卷 3071-3094页

作者： Dang Thi, Phuc Nguyen Dang, Hoang Thi Doan Huu, Phuc Dau Sy, Hieu Department of Computer Science Faculty of Information Technology Industrial University of Ho Chi Minh City 12 Nguyen Van Bao Ho Chi Minh City7000 Viet Nam Department of Applied Physics Faculty of Applied Science University of Technology - Viet Nam National University HCMC To Hien Thanh Ho Chi Minh City7000 Viet Nam

Optimizing camera information storage is a critical issue due to the increasing data volume and a large number of daily surveillance videos. In this study, we propose a deep learning-based system for efficient data storage. Videos captured by cameras are classified into four categories: no action, normal action, human action, and dangerous action. Videos without action or with normal action are stored temporarily and then deleted to save storage space. Videos with human action are stored for easy retrieval, while videos with dangerous action are promptly alerted to users. In the paper, we propose two approaches using deep learning models to address the video classification problem. The first approach is a separate approach, where pretrained CNN models extract features from video frame images. These features are then passed through RNN, Transformer models to extract relationships between them. The goal of this approach is to delve into extracting features of objects in the video. The proposed models include VGG16, InceptionV3 combined with LSTM, BiLSTM, Attention, and Vision Transformer. The next approach combines CNN and LSTM layers simultaneously through models like ConvLSTM and LRCN. This approach aims to help the model simultaneously extract object features and their relationships, with the goal of reducing model size, accelerating the training process, and increasing object recognition speed when deployed in the system. In Approach 1, we construct and refine network architectures such as VGG16+LSTM, VGG16+Attention+LSTM, VGG16+BiLSTM, VGG16+ViT, InceptionV3+LSTM, InceptionV3+Attention+LSTM, InceptionV3+BiLSTM. In Approach 2, we build a new network architecture based on the ConvLSTM and LRCN model. The training dataset, collected from real surveillance cameras, comprises 3315 videos labeled into four classes: no action (1018 videos), actions involving people (832 videos), dangerous actions (751 videos), and normal actions (714 videos). Experimental results show t

关键词： Deep learning

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A feature weighted K-nearest neighbor algorithm based on association rules

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Journal of Ambient Intelligence and Humanized Computing 2024年第7期15卷 2995-3008页

作者： Manzali, Youness Barry, Khalidou Abdoulaye Flouchi, Rachid Balouki, Youssef Elfar, Mohamed Laboratory of Applied Physics Computer Science and Statistics Faculty of Sciences Dhar El Mehraz Sidi Mohamed Ben Abdellah University Fez Morocco Laboratory of Microbial Biotechnology and Bioactive Molecules Science and Technologies Faculty Sidi Mohamed Ben Abdellah University Fez Morocco Science and Technologies Faculty University Hassan 1st Settat Morocco

K-nearest neighbors (kNN) is a popular machine learning algorithm because of its clarity, simplicity, and efficacy. kNN has numerous drawbacks, including ignoring issues like class distribution, feature relevance, neighbor contribution, and the number of individuals for each class. In particular, some features could be more important than others for classifying a data point, and increasing their weight in the distance computation can make the kNN algorithm more accurate. Researchers propose different feature weightings, such as correlation-based feature selection, mutual information, and chi-square feature selection. This paper presents a new feature weighting technique based on association rules and information gain. The proposed approach gives a good performance compared to other similar methods. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Association rules

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Production and decay of hyperons in p+p reactions measured with HADES 7

Production and decay of hyperons in p+p reactions measured w...

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7th Edition Workshop on FAIR Next Generation Scientists, FAIRness 2022

作者： Sumara, Konrad Salabura, Piotr Lalik, Rafal Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Lojasiewicza 11 Krakáw Poland

The internal structure of nucleons and interactions between their components have been debated ever since the existence of quarks was postulated. A lot of experimental evidence has been gathered, indicating that nucleons and their excited states are not simple static quark states but are significantly influenced by the dynamics of baryon-meson interactions. In this context it is interesting to extend internal structure studies to hyperons, particles where one light quark of a nucleon is replaced by a heavier strange quark, e.g. Λ, Σ or Σ+(1385), or excited states such as: Λ(1520) or Λ(1405). Many competing models, including also those based on the dynamical state generation, try to describe the internal structure of these hyperons. The predictions are sensitive to e.g. relative widths of radiative decays of hyperons. In order to discriminate between models, it is helpful to measure radiative decays (with emission of a γ or e+e-pairs) and hadronic decays, e.g. Λ(1520) → Σ+(1385) π-, ?(1405) → Σ π. These decays are largely unexplored at present and are the motivation for the project presented in this talk. The goal of this project is to study the production of Σ+(1385), Λ(1520) and Λ(1405) hyperons produced in proton-proton at beam energies ranging from 3.5 GeV to 4.5 GeV with HADES detector at FAIR. The analysis described in this work is a first step in this direction and presents results of Σ+(1385) production in p + p at 3.5 GeV. © 2023 Sissa Medialab Srl. All rights reserved.

关键词： Excited states

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Hadron physics results at KLOE-2 experiment 10

Hadron Physics results at KLOE-2 experiment

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10th International Workshop on Chiral Dynamics, CD 2021

作者： del Rio, Elena Perez Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University S. Lojasiewicza 11 Kraków30-348 Poland

KLOE and KLOE-2 data (almost 8 fb−1) constitute the largest sample ever collected at an electron-positron collider operating at the φ peak resonance. In total it corresponds to the production of about 24 billion of φ mesons whose decays include about 8 billion pairs of neutral K mesons and 300 million η mesons. A wide hadron physics program, investigating rare meson decays, γ − γ interaction, dark forces and hadronic cross section, is thus carried out by the KLOE-2 Collaboration. The latest results and present analysis of the KLOE-2 collaboration are presented. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Hadrons

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Impact of Time Resolution and Window Length on the Capture of Frequency Variations and Events

Impact of Time Resolution and Window Length on the Capture o...

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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Polajžer, Boštjan Mohammadi, Younes Saremi, Amin University of Maribor Faculty of Electrical Engineering and Computer Science Maribor Slovenia Umeå University Department of Applied Physics and Electronics Umeå Sweden

ISBN: (纸本)9789531842976

Power-quality standards provide limited guidance on frequency quality for short time scales, such as less than one hour. Capturing frequency variations and events requires high time resolutions, e.g., 0.1 seconds or less, resulting in significant data storage requirements. However, power-quality monitors typically report averaged values at intervals of 10 minutes, 15 minutes, or one hour, depending on the disturbance type. To address these challenges, we propose calculating statistic indices from high-resolution data within a 15-minute or one-hour window length, thus avoiding storing high-resolution data. We apply the basic statistic indices to frequency data measured in Finland for a single day in June 2023, demonstrating their effectiveness in capturing frequency variations and two significant events during that day. © 2024 IEEE.

关键词： Time measurement

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Findings of the Third Shared Task on Multilingual Coreference Resolution 7

Findings of the Third Shared Task on Multilingual Coreferenc...

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7th Workshop on Computational Models of Reference, Anaphora and Coreference, CRAC 2024

作者： Novák, Michal Dohnalová, Barbora Konopík, Miloslav Nedoluzhko, Anna Popel, Martin Pražák, Ondřej Sido, Jakub Straka, Milan Žabokrtský, Zdeněk Zeman, Daniel Charles University Faculty of Mathematics and Physics Institute of Formal and Applied Linguistics Prague Czech Republic University of West Bohemia Faculty of Applied Sciences Department of Computer Science and Engineering Pilsen Czech Republic

ISBN: (纸本)9798891761711

The paper presents an overview of the third edition of the shared task on multilingual coreference resolution, held as part of the CRAC 2024 workshop. Similarly to the previous two editions, the participants were challenged to develop systems capable of identifying mentions and clustering them based on identity coreference. This year’s edition took another step towards real-world application by not providing participants with gold slots for zero anaphora, increasing the task’s complexity and realism. In addition, the shared task was expanded to include a more diverse set of languages, with a particular focus on historical languages. The training and evaluation data were drawn from version 1.2 of the multilingual collection of harmonized coreference resources CorefUD, encompassing 21 datasets across 15 languages. 6 systems competed in this shared task. © 2024 Association for Computational Linguistics.

关键词： Computational linguistics

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DISTANCE BETWEEN SPECIES BY CONFUSION OPERATORS OF MULTI-CLASS CLASSIFIERS

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UPB Scientific Bulletin, Series A: applied Mathematics and physics 2025年第1期2025卷 171-182页

作者： Tarbă, Nicolae Irimescu, Ionela N. Pleavă, Ana M. Scarlat, Eugen N. Mihăilescu, Mona Doctoral School Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by the classes. Operation in the confusion domain allows us to use the distance as evaluation metric of the closeness of the relevant properties carried by the classes. We applied the method to semiquantitatively evaluate the effects of X-ray and carbon ion radiation on cultured SW1353 chondrosarcoma cells with respect to the non-irradiated reference. We prove that it is possible to draw useful information on the strength of cells nuclei changes. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Radiation effects

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Evaluation and Comparison of Emotionally Evocative Image Augmentation Methods 28th

Evaluation and Comparison of Emotionally Evocative Image Aug...

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28th International Conference on Knowledge Based and Intelligent information and Engineering Systems, KES 2024

作者： Ignatowicz, Jan Kutt, Krzysztof Nalepa, Grzegorz J. Jagiellonian Human-Centered AI Lab Mark Kac Center for Complex Systems Research Institute of Applied Computer Science Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Lojasiewicza 11 Kraków30-348 Poland

Experiments in affective computing are based on stimulus datasets that, in the process of standardization, receive metadata describing which emotions each stimulus evokes. In this paper, we explore an approach to creating stimulus datasets for affective computing using generative adversarial networks (GANs). Traditional dataset preparation methods are costly and time consuming, prompting our investigation of alternatives. We conducted experiments with various GAN architectures, including Deep Convolutional GAN, Conditional GAN, Auxiliary Classifier GAN, Progressive Augmentation GAN, and Wasserstein GAN, alongside data augmentation and transfer learning techniques. Our findings highlight promising advances in the generation of emotionally evocative synthetic images, suggesting significant potential for future research and improvements in this domain. © 2024 The Authors.

关键词： Generative adversarial networks

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Odd-even effects in the structure and properties of aryl-substituted aliphatic self-assembled monolayers

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Nano Research 2024年第5期17卷 4231-4243页

作者： Piotr Cyganik Andreas Terfort Michael Zharnikov Jagiellonian University Faculty of PhysicsAstronomy and Applied Computer ScienceSmoluchowski Institute of PhysicsŁojasiewicza 1130-348 KrakówPoland Institut für Anorganische und Analytische Chemie Universität FrankfurtMax-von-Laue-Straße 760438 FrankfurtGermany Applied Physical Chemistry Heidelberg UniversityIm Neuenheimer Feld 25369120 HeidelbergGermany

Self-assembled monolayers(SAMs)represent an important tool in context of nanofabrication and molecular engineering of surfaces and *** properties of functional SAMs depend not only on the character of the tail groups at the SAM-ambient interface,but are also largely defined by their *** its turn,the latter parameter results from a complex interplay of the structural forces and a variety of other factors,including so called odd-even effects,*** of the SAM structure and properties on the parity of the number(odd or even)of individual building blocks in the backbone of the SAM *** most impressive manifestation of the odd-even effects is the structure of aryl-substituted alkanethiolate SAMs on Au(111)and Ag(111),in which,in spite of the fact that the intermolecular interaction is mostly determined by the aryl part of the monolayers,one observes a pronounced dependence of molecular inclination and,consequently,the packing density of the SAM-forming molecules on the parity of number of methylene units in the alkyl *** we review the properties of the above systems as well as address fundamental reasons behind the odd-even effects,including the existence of a so-called bending potential,which is frequently disregarded in analysis of the structure-building *** generality of the odd-even effects in SAMs is additionally supported by the recent data for SAMs on GaAs,scanning tunneling microscopy data for SAMs on Ag(111),and the data for the monolayers with selenolate and carboxyl anchoring groups on Au(111)and Ag(111).The implications of these effects in terms of the control over the packing density and orientation of the tail groups at the SAM-ambient interface,structural perfection,polymorphism,temperature-driven phase transitions,and SAM stability toward such factors as ionizing radiation,exchange reaction,and electrochemical desorption are *** implications place the odd-even effects as an important tool

关键词： self-assembled monolayers molecular films surface and interface engineering odd-even-effects

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