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40th International Symposium on Theoretical Aspects of computer Science, STACS 2023

作者： Koana, Tomohiro Faculty IV Institute of Software Engineering and Theoretical Computer Science Algorithmics and Computational Complexity Technische Universität Berlin Germany

ISBN: (纸本)9783959772662

In this work, we study the Induced Matching problem: Given an undirected graph G and an integer , is there an induced matching M of size at least ? An edge subset M is an induced matching in G if M is a matching such that there is no edge between two distinct edges of M. Our work looks into the parameterized complexity of Induced Matching with respect to "below guarantee" parameterizations. We consider the parameterization u − for an upper bound u on the size of any induced matching. For instance, any induced matching is of size at most n/2 where n is the number of vertices, which gives us a parameter n/2 − . In fact, there is a straightforward 9n/2− · nO(1)-time algorithm for Induced Matching [Moser and Thilikos, J. Discrete Algorithms]. Motivated by this, we ask: Is Induced Matching FPT for a parameter smaller than n/2 − ? In search for such parameters, we consider MM(G) − and IS(G) − , where MM(G) is the maximum matching size and IS(G) is the maximum independent set size of G. We find that Induced Matching is presumably not FPT when parameterized by MM(G) − or IS(G) − . In contrast to these intractability results, we find that taking the average of the two helps – our main result is a branching algorithm that solves Induced Matching in 49(MM(G)+IS(G))/2− · nO(1) time. Our algorithm makes use of the Gallai–Edmonds decomposition to find a structure to branch on. © Tomohiro Koana.

关键词： Parameterization

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From Data to Diagnosis: Investigating Approaches in Mental Illness Detection 2

From Data to Diagnosis: Investigating Approaches in Mental I...

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2nd International Conference of Intelligent Methods, Systems and Applications, IMSA 2024

作者： Montasser, Reem Kadry Mazen, Sherif A. Helal, Iman M. A. October University for Modern Sciences and Arts Faculty of Computer Science Software Engineering Department Giza Egypt Cairo University Faculty of Computers and Artificial Intelligence Information Systems Department Giza Egypt

ISBN: (纸本)9798350362633

Mental illness is a considerable global public health problem, impacting both individual well-being and society's health. The growing popularity of social media and the increase of other data sources led to more research interest in detecting mental illness with a particular focus on utilizing and fusing emotional information. Artificial intelligence techniques like natural language processing and others, have shown encouraging improvements in recognizing complex relationships in a wide range of textual data, including clinical notes, social media posts, and interviews. In this paper, we assess the different branches of artificial intelligence based on previous research in mental illness detection, discussing methods, trends, challenges, and future research directions. © 2024 IEEE.

关键词： Adversarial machine learning

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Enhancing breast cancer histopathological image classification using attention-based high order covariance pooling

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Neural Computing and Applications 2024年第36期36卷 23275-23293页

作者： Waqas, Muhammad Ahmed, Amr Maul, Tomas Liao, Iman Yi School of Computer Science Faculty of Science and Engineering University of Nottingham Malaysia Campus Selangor Dar ul Ehsan Semenyih43500 Malaysia Department of Software Engineering University of Malakand Khyber Pakhtunkhwa Lower Dir Chakdara18800 Pakistan Department of Computer Science Edge Hill University Lancashire L39 4QP United Kingdom School of Computer Science Faculty of Science University of Nottingham NottinghamNG8 1BB United Kingdom

Breast cancer, the most common cancer affecting female patients, presents serious challenges for proper detection. Although computer-aided diagnostic techniques have progressed, their accuracy and efficacy remain limited. To overcome these challenges, we introduce DHA-Net, a new deep learning system that combines an effective attention module (EAM) and a high-order pooling layer with a ResNet-18 backbone. DHA-Net is tested using three well-known breast cancer histopathology image datasets: BreakHis, BACH2018, and a closely related Kaggle-Breast cancer histopathology dataset. Our experiments show that DHA-Net not only improves on existing state-of-the-art approaches, but significantly outperforms them in classifying breast cancer images. This work emphasizes the novel combination of an EAM with high-order pooling, demonstrating DHA-Net’s potential to improve diagnostic accuracy and serve as a more effective tool for medical imaging applications. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Lung cancer

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Collaborative learning-based inter-dependent task dispatching and co-location in an integrated edge computing system

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Digital Communications and Networks 2024年第6期10卷 1837-1850页

作者： Uchechukwu Awada Jiankang Zhang Sheng Chen Shuangzhi Li Shouyi Yang School of Software Henan Institute of Science and TechnologyXinxiang 453003China School of Electrical and Information Engineering Zhengzhou UniversityZhengzhou 450001China Department of Computing and Informatics Bournemouth UniversityPoole BH125BBUK School of Electronics and Computer Science University of SouthamptonSouthampton SO171BJUK Faculty of Information Science and Engineering Ocean University of ChinaQingdao 266100China

Recently,several edge deployment types,such as on-premise edge clusters,Unmanned Aerial Vehicles(UAV)-attached edge devices,telecommunication base stations installed with edge clusters,etc.,are being deployed to enable faster response time for latency-sensitive *** fundamental problem is where and how to offload and schedule multi-dependent tasks so as to minimize their collective execution time and to achieve high resource *** approaches randomly dispatch tasks naively to available edge nodes without considering the resource demands of tasks,inter-dependencies of tasks and edge resource *** approaches can result in the longer waiting time for tasks due to insufficient resource availability or dependency support,as well as provider ***,we present Edge Colla,which is based on the integration of edge resources running across multi-edge *** Colla leverages learning techniques to intelligently dispatch multidependent tasks,and a variant bin-packing optimization method to co-locate these tasks firmly on available nodes to optimally utilize *** experiments on real-world datasets from Alibaba on task dependencies show that our approach can achieve optimal performance than the baseline schemes.

关键词： Edge computing Collaborative learning Resource utilization Execution time Edge federation Gang scheduling

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Efficiency in Multi-Channel Data Transmission Systems with Priority Service Under High Load

Efficiency in Multi-Channel Data Transmission Systems with P...

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International Russian Automation Conference (RusAutoCon)

作者： Sodnom Lygdenov Faculty of Software Engineering and Computer Engineering ITMO University Saint Petersburg Russia

ISBN: (数字)9798350349818

ISBN: (纸本)9798350349825

The subject of research. Analysis of the influence of priority service in multi-channel data transmission systems characterized by limited storage capacity and high load, taking into account the non-stationary characteristics of the intensity of packet arrivals and service time. Method. The functional characteristics of the multi-channel system were calculated and analyzed using simulation methods and mathematical statistics. Main results. A simulation model of a multi-channel system with priority service has been developed, designed to evaluate the functional characteristics of the system under high load. Experiments have been conducted to study the impact of priority service on delays and packet losses of heterogeneous traffic. Practical significance. The results obtained can be used in the design of multi-threaded data transmission systems operating under conditions of high heterogeneous load.

关键词： Analytical models System performance Packet loss Quality of service Maintenance Telecommunications Data communication Sustainable development Load modeling Network systems

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Priority Service in Data Transmission Networks with Non-Stationary Flows

Priority Service in Data Transmission Networks with Non-Stat...

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International Russian Smart Industry Conference (SmartIndustryCon)

作者： Sodnom Lygdenov Faculty of Software Engineering and Computer Engineering ITMO University Saint Petersburg Russia

The subject of research. Analysis of the impact of priority data transmission in high-load multi-channel systems represented as a mass service system with request prioritization under different variations in the distribution of random variables of packet arrival intensity in the network and service time in the channels. Method. The study of the influence of priorities on the efficiency of data transmission in multi-channel systems was carried out using simulation and mathematical statistics methods. Main results. The method of numerical calculation of time parameters based on the simulation model of multi-channel data transmission system with heterogeneous load is proposed. Simulation experiments evaluating the impact of priority data transmission at different coefficients of variation of packet intensity and service time in the channels on the time characteristics of the multi-channel system are conducted. Practical significance. The obtained results can be applied to the design of multi-channel computer systems of high load data transmission, providing the optimal use of priorities to improve the efficiency of data transmission.

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256 Metaverse Records Dataset 24

256 Metaverse Records Dataset

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32nd ACM International Conference on Multimedia, MM 2024

作者： Steinert, Patrick Wagenpfeil, Stefan Frommholz, Ingo Hemmje, Matthias L. Faculty of Mathematics and Computer Science University of Hagen Hagen Germany Faculty of Business Computing and Software Engineering Pfh University of Applied Sciences Göttingen Germany School of Mathematics and Computer Science University of Wolverhampton Wolverhampton United Kingdom

ISBN: (纸本)9798400706868

The metaverse is a developing field that crosses several areas of multimedia research. In this paper, we introduce the 256-MetaverseRecords dataset, a novel and extensive collection of annotated screen recordings in the form of videos from various virtual worlds of the metaverse. We describe the process of creating the dataset, the quality criteria for the annotations, and the exploration of the dataset. We also show four experiments to evaluate the performance of different feature extraction methods for Metaverse Recordings (MVRs): MVR segmentation, audio event detection, and object and interaction detection based on this dataset. Our results demonstrate that existing methods have limitations and leave challenges in dealing with the diversity and complexity of metaverse data, and that more research is needed to develop metaverse-specific techniques. Our dataset can serve as a valuable resource for the research community and foster the development of new applications and solutions for the metaverse. © 2024 Owner/Author.

关键词： dataset

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Research and Development of Kubernetes Operator for Lightweight Multi-Access Edge Computing Platform Simulator

Research and Development of Kubernetes Operator for Lightwei...

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2025 Systems of Signals Generating and Processing in the Field of on Board Communications, SOSG 2025

作者： Filianin, Ivan Borisov, Nikita Bogatyrev, Vladimir Itmo University Faculty of Software Engineering and Computer Engineering St. Petersburg Russia Itmo University Faculty of Infocommunication Technologies St. Petersburg Russia Saint-Petersburg State University of Aerospace Instrumentation Department of Information Systems Security St. Petersburg Russia

ISBN: (纸本)9798331532635

This paper addresses the problem of deploying complex systems in Kubernetes clusters. It discusses using the OperatorSDK framework supported by RedHat as a basis for implementing the Kubernetes operator for Lightweight MultiAccess Edge Computing Platform Simulator (LWMECPS) deployment. Special attention is given to the operator Kubernetes architecture and how to use Operator Lifecycle Manager (OLM) to continuously deploy LWMECPS and machine learning models for it. © 2025 IEEE.

关键词： Edge computing

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Behavior Trees and State Machines in Robotics Applications

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IEEE Transactions on software engineering 2023年第9期49卷 4243-4267页

作者： Ghzouli, Razan Berger, Thorsten Johnsen, Einar Broch Wasowski, Andrzej Dragule, Swaib Chalmers University of Technology Department of Computer Science and Engineering Gothenburg40530 Sweden Ruhr University Bochum Faculty of Computer Science Bochum44801 Germany Chalmers University of Gothenburg Department of Computer Science and Engineering Gothenburg40530 Sweden University of Oslo Department of Informatics Oslo0316 Norway IT University of Copenhagen Software Development Group Copenhagen2300 Denmark

Autonomous robots combine skills to form increasingly complex behaviors, called missions. While skills are often programmed at a relatively low abstraction level, their coordination is architecturally separated and often expressed in higher-level languages or frameworks. State machines have been the go-to language to model behavior for decades, but recently, behavior trees have gained attention among roboticists. Originally designed to model autonomous actors in computer games, behavior trees offer an extensible tree-based representation of missions and are claimed to support modular design and code reuse. Although several implementations of behavior trees are in use, little is known about their usage and scope in the real world. How do concepts offered by behavior trees relate to traditional languages, such as state machines? How are concepts in behavior trees and state machines used in actual applications? This paper is a study of the key language concepts in behavior trees as realized in domain-specific languages (DSLs), internal and external DSLs offered as libraries, and their use in open-source robotic applications supported by the Robot Operating System (ROS). We analyze behavior-tree DSLs and compare them to the standard language for behavior models in robotics: state machines. We identify DSLs for both behavior-modeling languages, and we analyze five in-depth. We mine open-source repositories for robotic applications that use the analyzed DSLs and analyze their usage. We identify similarities between behavior trees and state machines in terms of language design and the concepts offered to accommodate the needs of the robotics domain. We observed that the usage of behavior-tree DSLs in open-source projects is increasing rapidly. We observed similar usage patterns at model structure and at code reuse in the behavior-tree and state-machine models within the mined open-source projects. We contribute all extracted models as a dataset, hoping to inspire the commu

关键词： Modeling languages

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Traffic Management in Internet of Vehicles Using Improved Ant Colony Optimization

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computers, Materials & Continua 2023年第6期75卷 5379-5393页

作者： Abida Sharif Imran Sharif Muhammad Asim Saleem Muhammad Attique Khan Majed Alhaisoni Marriam Nawaz Abdullah Alqahtani Ye Jin Kim Byoungchol Chang Department of Computer Science COMSATS University IslamabadPakistan Faculty of Computing Riphah International UniversityFaisalabadPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science UET TaxilaTaxilaPakistan Department of Software Engineering UET TaxilaTaxilaPakistan Software Engineering Department College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942KSA Department of Computer Science Hanyang UniversitySeoul04763Korea Center for Computational Social Science Hanyang UniversitySeoul04763Korea

The Internet of Vehicles(IoV)is a networking paradigm related to the intercommunication of vehicles using a *** a dynamic network,one of the key challenges in IoV is traffic management under increasing vehicles to avoid ***,optimal path selection to route traffic between the origin and destination is *** research proposed a realistic strategy to reduce traffic management service response time by enabling real-time content distribution in IoV systems using heterogeneous network ***,this work proposed a novel use of the Ant Colony Optimization(ACO)algorithm and formulated the path planning optimization problem as an Integer Linear Program(ILP).This integrates the future estimation metric to predict the future arrivals of the vehicles,searching the optimal *** the mobile nature of IOV,fuzzy logic is used for congestion level estimation along with the ACO to determine the optimal *** model results indicate that the suggested scheme outperforms the existing state-of-the-art methods by identifying the shortest and most cost-effective ***,this work strongly supports its use in applications having stringent Quality of Service(QoS)requirements for the vehicles.

关键词： Internet of vehicles internet of things fuzzy logic optimization path planning

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