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Afra: An Eclipse-Based Tool with Extensible Architecture for Modeling and Model Checking of Rebeca Family Models 1

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10th IPM International Conference on Fundamentals of Software Engineering, FSEN 2023

作者： Khamespanah, Ehsan Sirjani, Marjan Khosravi, Ramtin School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Computer Science Reykjavik University Reykjavik Iceland School of Innovation Design and Engineering Mälardalen University Västerås Sweden

ISBN: (数字)9783031424410

ISBN: (纸本)9783031424403

Afra is an Eclipse-based tool for the modeling and model checking of Rebeca family models. Together with the standard enriched editor, easy to trace counter-example viewer, modular temporal property definition, exporting a model and its transition system to some other formats facilities are features of Afra. Rebeca family provides actor-based modeling languages which are designed to bridge the gap between formal methods and software engineering. Faithfulness to the system being modeled, and the usability of Rebeca family languages help in ease of modeling and analysis of the model, together with the synthesis of the system based on the model. In this paper, architectural decisions and design strategies we made in the development of Afra are presented. This makes Afra an extensible and reusable application for the modeling and analysis of Rebeca family models. Here, we show how different compilers can be developed for the family of languages which are the same in general language constructs but have some minor differences. Then we show how the model checking engine for these different languages is designed. Despite the fact that Afra has a layered object-oriented design and is developed in Java technology, we use C++ codes for developing its model checking for the performance purposes. This decision made the design of the application even harder. © 2023, IFIP International Federation for Information Processing.

关键词： Model checking

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Software Aided Approach for Constrained Optimization Based on QAOA Modifications 1

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23rd International Conference on Computational science, ICCS 2023

作者： Lamża, Tomasz Zawalska, Justyna Sterzel, Mariusz Rycerz, Katarzyna Institute of Computer Science AGH al. Mickiewicza 30 Krakow30-059 Poland Academic Computer Center Cyfronet AGH ul. Nawojki 11 Krakow30-950 Poland

ISBN: (数字)9783031360305

ISBN: (纸本)9783031360299

We present two variants of the QAOA modification for solving constrained combinatorial problems. The results presented in this paper were obtained using the QHyper framework, which we developed specifically for this purpose. More specifically, we use the created framework to compare the QAOA results with its two modifications, namely: Weight-Free QAOA (WF-QAOA) and Hyper QAOA (H-QAOA). Additionally, we compare the Basin-hopping global optimization method for subsequent sampling of the initial points for the proposed QAOA modifications with a simple Random Search. The results obtained for the Knapsack Problem indicate that the proposed solution outperforms the original QAOA algorithm and can be promising for QUBO, where adjusting the relative importance of the cost function and the constraints is a significant challenge. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Constrained optimization

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Named Entity Recognition to Extract Knowledge from Clinical Texts 4th

Named Entity Recognition to Extract Knowledge from Clinica...

引用

4th International Conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

作者： Scarpino, Ileana Vallelunga, Rosarina Luzza, Francesco Department of Medical and Surgical Sciences University of Catanzaro Catanzaro Italy Department of Health Science University of Catanzaro Catanzaro Italy

ISBN: (纸本)9783031812460

Clinical texts encompass a wide range of information such as patient’s history, disease diagnosis and prescribed drugs, reflecting details and nuances that are valuable in providing knowledge. In the present study, a Natural Language Processing approach, specifically Named Entity Recognition (NER), is applied to extract important concepts from gastroenterology clinical texts. NER is a task of text analytics to identify, in written documents, named entities ranging from general concepts to information in specific fields. The application is performed through freely available Python packages of the spaCy library adapted to the English language. Although the spaCy’s NER is generic, models trained in the clinical domain are used to identify categories belonging to the medical sector of interest. In particular, the main goal is to find as much entities as possible by paying attention to major bowel diseases, such as Ulcerative Colitis and Crohn’s disease. We performed two experiments, the first one involves the use of the ScispaCy package for scientific text processing. The second one applies Med7 that is a spaCy NER model for labeling drug information trained for identification of seven medication-related concepts, dosage, drug names, duration, form, frequency, route of administration, and strength. The results show that two approaches applied for NER analysis perform well to extract knowledge from gastroenterology clinical texts. The results obtained will allow to evaluate the efficiency of the proposed methodology and to analyze, through the extracted entities, the profile and aspects of the diseases considered and the associated drugs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Gastroenterology

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Generalization Gap in Data Augmentation: Insights from Illumination 27th

Generalization Gap in Data Augmentation: Insights from Ill...

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27th International Conference on Pattern Recognition, ICPR 2024

作者： Xiao, Jianqiang Guo, Weiwen Liu, Junfeng Li, Mengze South China University of Technology Guangzhou China Co. Ltd. Guangzhou China Co. Ltd. Guangzhou China Research Center for Frontier Fundamental Studies Zhejiang Lab Hangzhou China

ISBN: (纸本)9783031784439

In the field of computer vision, data augmentation is widely used to enrich the feature complexity of training datasets with deep learning techniques. However, regarding the generalization capabilities of models, the difference in artificial features generated by data augmentation and natural visual features has not been fully revealed. This study introduces the concept of "visual representation variables" to define the possible visual variations in a task as a joint distribution of these variables. We focus on the visual representation variable "illumination", by simulating its distribution degradation and examining how data augmentation techniques enhance model performance on a classification task. Our goal is to investigate the differences in generalization between models trained with augmented data and those trained under real-world illumination conditions. Results indicate that after applying various data augmentation methods, model performance has significantly improved. Yet, a noticeable generalization gap still exists after utilizing various data augmentation methods, emphasizing the critical role of feature diversity in the training set for enhancing model generalization. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： computer Vision Data Augmentation Generalization

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A Real-Time Support with Haptic Feedback for Safer Driving Using Monocular Camera 23rd

A Real-Time Support with Haptic Feedback for Safer Driving...

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23rd International Conference of the Italian Association for Artificial Intelligence, AIxIA 2024

作者： De Magistris, Giorgio Guercio, Lorenzo Starna, Francesco Russo, Samuele Kryvinska, Natalia Napoli, Christian Department of Computer Control and Management Engineering Sapienza University of Rome via Ariosto 25 Rome00185 Italy Department of Psychology Sapienza University of Rome via Dei Marsi 78 Roma00185 Italy Faculty of Management Comenius University in Bratislava Bratislava Slovakia

ISBN: (纸本)9783031806063

Each year, car accidents impact billions of people, resulting in numerous casualties. Consequently, road safety remains a top priority for nations worldwide. This project aims to enhance driver safety through a feedback system that relies solely on a monocular camera mounted atop the vehicle. The proposed system is a real-time application designed to warn drivers of imminent road hazards, which are classified by their level of risk. Our method employs various computer vision techniques and incorporates a simple 2D-3D correspondence to estimate the longitudinal and lateral distances of objects ahead of the vehicle, under certain simplifying assumptions. The system conducts a comprehensive danger analysis by evaluating potential hazards within the vehicle’s path. Depending on the danger level, warnings are delivered to the driver with varying degrees of invasiveness, using haptic feedback. The proposed method was tested on the KITTI dataset, yielding positive results. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Hazards

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Constrained Graph Searching on Trees 1

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17th International Joint Conference on Theoretical computer science - Frontier of Algorithmic Wisdom, IJTCS-FAW 2023

作者： Wang, Lusheng Yang, Boting Zhan, Zhaohui Department of Computer Science City University of Hong Kong Kowloon Tong Hong Kong Department of Computer Science University of Regina ReginaSK Canada City University of Hong Kong Shenzhen Research Institution Shenzhen China

ISBN: (数字)9783031393440

ISBN: (纸本)9783031393433

Megiddo et al. (1988) introduced the edge searching problem, which is to find the minimum number of searchers to capture the robber in the edge searching model. Dyer et al. (2008) introduced the fast searching problem that is to find the minimum number of searchers to capture the robber in the fast searching model. In this paper, we consider these two graph searching problems under some constraints. One constraint is that a subset of vertices, called start vertices, are initially occupied by searchers before we place additional searchers on the graph. Another constraint is that some of the searchers must end their search at certain vertices called halt vertices. We focus on trees with n vertices. Let k be the number of times to move searchers from start vertices. For the edge searching problem, we give an O(kn)-time algorithm for computing the edge search number of a tree that contains only start vertices or only halt vertices. For a tree that contains both start vertices and halt vertices, we present an O(n2) -time algorithm to compute the edge search number. We show that all these problems are monotonic. For the fast searching problem, we propose a linear-time algorithm for computing the fast search number of a tree that contains only start vertices or only halt vertices. For a tree with n vertices that contains s start vertices and h halt vertices, we give an O((s+ h) n) -time algorithm to compute the fast search number. © 2023, Springer Nature Switzerland AG.

关键词： Clustering algorithms

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FlyAI - The Next Level of Artificial Intelligence is Unpredictable! Injecting Responses of a Living Fly into Decision Making 9th

FlyAI - The Next Level of Artificial Intelligence is Unpred...

引用

9th International Workshop on Sensor-Based Activity Recognition and Artificial Intelligence, iWOAR 2024

作者： Matthies, Denys J. C. Schlonsak, Ruben Zhuang, Hanzhi Song, Rui Technical University of Applied Sciences Lübeck Lübeck Germany Fraunhofer IMTE Lübeck Germany East China University of Science and Technology Shanghai China

ISBN: (纸本)9783031808555

In this paper, we introduce a new type of bionic AI that enhances decision-making unpredictability by incorporating responses from a living fly. Traditional AI systems, while reliable and predictable, lack nuanced and sometimes unseasoned decision-making seen in humans. Our approach uses a fly’s varied reactions, to tune an AI agent in the game of Gobang. Through a study, we compare the performances of different strategies on altering AI agents and found a bionic AI agent to outperform human as well as conventional and white-noise enhanced AI agents. We contribute a new methodology for creating a bionic random function and strategies to enhance conventional AI agents ultimately improving unpredictability. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Random number generation

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ITAQ: Image Tag Recommendation Framework for Aquatic Species Integrating Semantic Intelligence via Knowledge Graphs 1

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5th Iberoamerican and the 4th Indo-American Knowledge Graphs and Semantic Web Conference, KGSWC 2023

作者： Nitin Hariharan, S.S. Deepak, Gerard Ortiz-Rodríguez, Fernando Panchal, Ronak Department of Computer Science and Engineering Alagappa Chettiar Government College of Engineering and Technology Karaikudi India Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Universidad Autonoma de Tamaulipas Ciudad Victoria Mexico Cognizant Technology Solutions Pune India

ISBN: (数字)9783031477454

ISBN: (纸本)9783031477447

In the era of Web 3.0, there is an increasing demand for social image tagging that incorporates knowledge-centric paradigms and adheres to semantic web standards. This paper introduces the ITAQ framework, a recommendation framework specifically designed for tagging images of aquatic species. The framework continuously integrates strategic knowledge curation and addition at various levels, encompassing topic modelling, metadata generation, metadata classification, ontology integration, and enrichment using knowledge graphs and sub graphs. The ITAQ framework calculates context trees from the enriched knowledge dataset using AdaBoost classifier which is a lightweight machine learning classifier. The CNN classifier handles the metadata, ensuring a well-balanced fusion of learning paradigms while maintaining computational feasibility. The intermediate derivation of context trees, computation of KL divergence, and Second Order Co-occurrence PMI contribute to semantic-oriented reasoning by leveraging semantic relatedness. The Ant Lion optimization is utilized to compute the most optimal solution by building upon the initial intermediate solution. Finally, the optimal solution is correlated with image tags and categories, leading to the finalization of labels and annotations. An overall precision of 94.07% with the lowest value of FDR of 0.06% and accuracy of 95.315 % has been achieved by the proposed work. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Adaptive boosting

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Parameterized Complexity of Generalizations of Edge Dominating Set 50th

Parameterized Complexity of Generalizations of Edge Domina...

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50th International Conference on Current Trends in Theory and Practice of computer science, SOFSEM 2025

作者： Aute, Shubhada Panolan, Fahad Saha, Souvik Saurabh, Saket Upasana, Anannya Department of Computer Science and Engineering IIT Hyderabad Kandi India School of Computer Science University of Leeds Leeds United Kingdom The Institute of Mathematical Sciences HBNI Chennai India University of Bergen Bergen Norway

ISBN: (纸本)9783031826696

The objective of this article is to propose two natural generalizations of covering edges by edges (Edge Dominating Set) and study these problems from the multivariate lens. The first is simply considering Edge Dominating Set on hypergraphs, called Hyperedge Dominating Set. Given a hypergraph H=(U,F), a set F⊆F is called a hyperedge dominating set if all hyperedges intersect with at least one hyperedge e∈F. The objective of the Hyperedge Dominating Set problem is to determine whether a hyperedge dominating set of size at most k exists. We find it quite surprising that such generalization is missing from the literature. The second extension we consider is the t-Path Edge Dominating Set problem. In this problem, the input consists of a graph G and an integer k, and the goal is to find a set P of at most k paths, each of length at most t, such that for every edge in G, at least one of its endpoints belongs to the vertex set V(P) for some P∈P. We show the following results and add to the literature on Edge Dominating Set. Hyperedge Dominating Set is FPT parameterized by k+d, where d is the maximum size of a hyperedge in the input hypergraph.A kernel of size O(kd) can be obtained for the Hyperedge Dominating Set problem, where d is the maximum size of a hyperedge in the input *** problem of finding a Hyperedge Dominating Set is computationally difficult;specifically it is W[2]-hard when parameterized by k. This hardness result holds even when each vertex is contained in at most 2 hyperedges and the intersection between any two hyperedges is at most 1.t-Path Edge Dominating Set is FPT when parameterized by k+t. Additionally, it has a kernel of size O(k3t3). Hyperedge Dominating Set is FPT parameterized by k+d, where d is the maximum size of a hyperedge in the input hypergraph. A kernel of size O(kd) can be obtained for the Hyperedge Dominating Set problem, where d is the maximum size of a hyperedge in the input hypergraph. The problem of finding a Hyperedge Dom

关键词： Parameterization

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Parallel Vectorized Implementations of Compensated Summation Algorithms 1

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14th International Conference on Parallel Processing and Applied Mathematics, PPAM 2022

作者： Dmitruk, Beata Stpiczyński, Przemyslaw Maria Curie-Sklodowska University Institute of Computer Science ul. Akademicka 9 Lublin20-031 Poland

ISBN: (数字)9783031304453

ISBN: (纸本)9783031304446

The aim of this paper is to show that Kahan’s and Gill-Møller compensated summation algorithms that allow to achieve high accuracy of summing long sequences of floating-point numbers can be efficiently vectorized and parallelized. The new implementation uses Intel AVX-512 intrinsics together with OpenMP constructs in order to utilize SIMD extension of modern multicore processors. We describe in detail the vectorization technique and show how to define custom reduction operators in OpenMP. Numerical experiments performed on a server with Intel Xeon Gold 6342 processors show that the new implementations of the compensated summation algorithms achieve much better accuracy than ordinary summation and their performance is comparable with the performance of the ordinary summation algorithm optimized automatically. Moreover, the experiments show that the vectorized implementation of the Gill-Møller algorithm is faster than the vectorized implementation of Kahan’s algorithm. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Digital arithmetic

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