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An Optimization Method Based on Drift Data and Time Series Information 20th

An Optimization Method Based on Drift Data and Time Series I...

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20th International Conference on Intelligent Computing (ICIC)

作者： Zhang, Qian Liu, Guanjun Jiang, Changjun Tongji Univ Dept Comp Sci Shanghai 201804 Peoples R China Tongji Univ Key Lab Embedded Syst & Serv Comp Shanghai 201804 Peoples R China Tongji Univ Shanghai Elect Transact & Informat Serv Collabora Shanghai 201804 Peoples R China

ISBN: (纸本)9789819755806;9789819755813

With the rapid development of Internet technology, a large amount of streaming data with potential application value will be generated on the Internet. Compared with traditional static data, streaming data typically exhibits the phenomenon of concept drift. This makes it challenging for traditional machine learning methods to uncover the potential application value of streaming data. To solve this problem, previous literature has proposed various methods, such as drift detection, ensemble learning, and sliding window methods, to address the issue of concept drift. However, most existing methods have ignored optimizing the initial data, resulting in the model being unable to accurately describe the distribution of current time data. This leads to a decrease in the model's accuracy. In this paper, we propose a novel optimization method called Optimization Method Based on Drift Data and Time Series Information (OMDD-TSI) to overcome the shortcomings of previous algorithms. Our optimization method is divided into two steps. First, determine the position of the drifting data in the initial data according to the Hoeffding's inequality, and supplement the drifting data based on the classification uncertainty. Secondly, our method assigns weights to drift data based on time series information. The results of a simulation experiment on 12 synthetic stream data and 5 real-world stream data show that the accuracy of the previous state-of-the-art methods has been improved to varying degrees after being optimized by our method (OMDD-TSI).

关键词： Streaming Data Concept Drift Machine Learning Optimization Method

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Topic Detection in COVID-19 Mortality Time Series 10th

Topic Detection in COVID-19 Mortality Time Series

引用

10th International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC)

作者： Grana, Manuel Badiola-Zabala, Goizalde Cano-Escalera, Guillermo Univ Basque Country UPV EHU Computat Intelligence Grp San Sebastian Spain

ISBN: (纸本)9783031611360;9783031611377

The mortality of COVID-19 has been analyzed from a predictive point of view, building models that failed to predict the medium and long term evolution of the time series. Looked in a retrospective way, it is possible to appreciate that the mortality impact of the pandemic was very different across countries. In this paper we deal with the discovery of representative patterns, i.e. topics in latent Dirichlet analysis (LDA), that may explain the observed mortality time series. The choice of the number of topics is a balance between the minimization of perplexity, and the avoidance of overfitting. We find that countries can be clustered according to the coefficients of the decomposition of their time series into topics, and that this decomposition has a geopolitical correspondence, i.e. countries with the same dominant topic representation belong to the same geographical and/or political domain.

关键词： Time series

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MUFASA: Multi-view Fusion and Adaptation Network with Spatial Awareness for Radar Object Detection 33rd

MUFASA: Multi-view Fusion and Adaptation Network with Spatia...

引用

33rd International Conference on Artificial Neural Networks and Machine Learning (ICANN)

作者： Peng, Xiangyuan Tang, Miao Sun, Huawei Bierzynski, Kay Servadei, Lorenzo Wille, Robert Tech Univ Munich Chair Design Automat Munich Germany Infineon Technol AG Neubiberg Germany China Univ Geosci Wuhan Wuhan Peoples R China

ISBN: (纸本)9783031723346;9783031723353

In recent years, approaches based on radar object detection have made significant progress in autonomous driving systems due to their robustness under adverse weather compared to LiDAR. However, the sparsity of radar point clouds poses challenges in achieving precise object detection, highlighting the importance of effective and comprehensive feature extraction technologies. To address this challenge, this paper introduces a comprehensive feature extraction method for radar point clouds. This study first enhances the capability of detection networks by using a plug-and-play module, GeoSPA. It leverages the Lalonde features to explore local geometric patterns. Additionally, a distributed multi-view attention mechanism, DEMVA, is designed to integrate the shared information across the entire dataset with the global information of each individual frame. By employing the two modules, we present our method, MUFASA, which enhances object detection performance through improved feature extraction. The approach is evaluated on the VoD and TJ4DRaDSet datasets to demonstrate its effectiveness. In particular, we achieve state-of-the-art results among radar-based methods on the VoD dataset with the mAP of 50.24%.

关键词： 3D object detection radar point cloud distributed multi-view attention Lalonde feature autonomous driving

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Using Matrix Sparsification to Solve Tropical Linear Vector Equations 1

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21st International Conference on Relational and Algebraic Methods in computer science (RAMiCS)

作者： Krivulin, Nikolai St Petersburg State Univ Univ Skaya Emb 7-9 St Petersburg 199034 Russia

ISBN: (数字)9783031682797

ISBN: (纸本)9783031682780;9783031682797

A linear vector equation in two unknown vectors is examined in the framework of tropical algebra dealing with the theory and applications of semirings and semifields with idempotent addition. We consider a two-sided equation where each side is a tropical product of a given matrix by one of the unknown vectors. We use a matrix sparsification technique to reduce the equation to a set of vector inequalities that involve row-monomial matrices obtained from the given matrices. An existence condition of solutions for the inequalities is established, and a direct representation of the solutions is derived in a compact vector form. To illustrate the proposed approach and to compare the obtained result with that of an existing solution procedure, we apply our solution technique to handle two-sided equations known in the literature. Finally, a computational scheme based on the approach to derive all solutions of the two-sided equation is discussed.

关键词： Idempotent semifield Two-sided linear vector equation Sparsified matrix Row-monomial matrix Complete solution

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Third Workshop on Augmented Intelligence in Technology-Assisted Review Systems (ALTARS) 46th

Third Workshop on Augmented Intelligence in Technology-Assis...

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46th European Conference on Information Retrieval (ECIR)

作者： Di Nunzio, Giorgio Maria Kanoulas, Evangelos Majumder, Prasenjit Univ Padua Dept Informat Engn Padua Italy Univ Amsterdam Informat Inst Fac Sci Amsterdam Netherlands DAIICT Gandhinagar India

ISBN: (纸本)9783031560682;9783031560699

In this third edition of the workshop on Augmented Intelligence in Technology-Assisted Review Systems (ALTARS), we focus on the capacity of building test collections for the evaluation of High-recall Information Retrieval (IR) systems which tackle challenging tasks that require the finding of (nearly) all the relevant documents in a collection. During the workshop, the organizers as well as the participants will discuss the problems of how to build and evaluate these types of systems and prepare a set of guidelines for a correct evaluation of those systems according to the current and future available datasets.

关键词： Technology-Assisted Review Systems Augmented Intelligence Evaluation Systematic Reviews eDiscovery

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Statement Graphs: Unifying the Graph Data Model Landscape 29th

Statement Graphs: Unifying the Graph Data Model Landscape

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29th International Conference on Database Systems for Advanced Applications (DASFAA)

作者： Gelling, Ewout Fletcher, George Schmidt, Michael Eindhoven Univ Technol Eindhoven Netherlands Amazon Web Serv Seattle WA USA

ISBN: (纸本)9789819755745;9789819755752

Graph database users today face a choice between two technology stacks. The Resource Description Framework (RDF), on one side, is a data model that was originally developed by the W3C to exchange interconnected data on the Web. On the other side, Labeled Property Graphs (LPGs) are geared towards efficient graph processing and have strong roots in developer and engineering communities. The two models look at graphs from different abstraction layers, expose - at the surface distinct features, come with different query languages, and are embedded into their own software ecosystems. Typical industry use cases call for applications which must bridge data systems under both stacks, leading to ad hoc and costly solutions. Towards remedying this pain point, we introduce a novel unifying graph data model called Statement Graphs, which combines the traits of RDF and LPG, and achieves interoperability at different levels: it (a) provides the ability to manage RDF and LPG data as a single, interconnected graph, (b) enables read querying over the integrated graph using any RDF or LPG query language, while (c) clearing the way for graph stack independent data exchange mechanisms. As a proof of concept, we present the 1G Playground;an in-memory DBMS built on the concepts of Statement Graphs, which facilitates storage of both RDF and LPG data, and allows for cross-model read querying using SPARQL and Gremlin.

关键词： database systems knowledge graphs graph modeling

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Monitoring Edge-Geodetic Sets in Graphs: Extremal Graphs, Bounds, Complexity 10th

Monitoring Edge-Geodetic Sets in Graphs: Extremal Graphs, Bo...

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10th International Conference on Algorithms and Discrete Applied Mathematics (CALDAM)

作者： Foucaud, Florent Marcille, Pierre-Marie Myint, Zin Mar Sandeep, R. B. Sen, Sagnik Taruni, S. Univ Clermont Auvergne CNRS Clermont Auvergne INP Mines St EtienneLIMOS F-63000 Clermont Ferrand France Univ Bordeaux CNRS Bordeaux INP LaBRIUMR 5800 F-33400 Bordeaux France Indian Inst Technol Dharwad Dharwad India

ISBN: (纸本)9783031522123;9783031522130

A monitoring edge-geodetic set, or simply an MEG-set, of a graph G is a vertex subset M subset of V (G) such that given any edge e of G, e lies on every shortest u-v path of G, for some u, v is an element of M. The monitoring edge-geodetic number of G, denoted by meg(G), is the minimum cardinality of such an MEG-set. This notion provides a graph theoretic model of the network monitoring problem. In this article, we compare meg(G) with some other graph theoretic parameters stemming from the network monitoring problem and provide examples of graphs having prescribed values for each of these parameters. We also characterize graphs G that have V (G) as their minimum MEG-set, which settles an open problem due to Foucaud et al. (CALDAM 2023). We also provide a general upper bound for meg(G) for sparse graphs in terms of their girth, and later refine the upper bound using the chromatic number of G. We examine the change in meg(G) with respect to two fundamental graph operations: clique-sum and subdivisions. In both cases, we provide a lower and an upper bound of the possible amount of changes and provide (almost) tight examples. Finally, we prove that the decision version of the problem of finding meg(G) is NP-complete even for the family of 3-degenerate, 2 apex graphs, improving the existing result by Haslegrave (Discrete Applied Mathematics 2023).

关键词： Geodetic set Monitoring edge geodetic set k-clique sum Subdivisions Chromatic number Girth Computational complexity

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Eco-SLAM: Resource-Efficient Edge-Assisted Collaborative Visual SLAM System 1

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23rd International Conference on Algorithms and Architectures for Parallel Processing (ICA3PP)

作者： Ou, Wenzhong Feng, Daipeng Luo, Ke Chen, Xu Sun Yat Sen Univ Sch Comp Sci & Engn Guangzhou Peoples R China

ISBN: (数字)9789819708598

ISBN: (纸本)9789819708581;9789819708598

Collaboration among multiple smart agents such as robots and UAVs is critical for the key tasks of simultaneous localization and mapping (SLAM), which are essential for many robotics applications. Visual SLAM maps by multiple collaborative agents can be promptly generated with the assistance of edge servers in proximity as the computing infrastructures. However, as the number of agents connected to an edge server continues growing, the pressure on bandwidth consumption and resource utilization also climbs dramatically, which may trigger the failure of map generation. To tackle these challenges, this article proposes Eco-SLAM, a resource-efficient edge-assisted collaborative multi-agent visual SLAM system. Eco-SLAM has been designed to enable large-scale parallelism in SLAM framework and optimized for use in both edge servers and intelligent agents. The unique Core-tr and CoMap library design ensures efficient utilization of resources and consistent data. Additionally, Eco-SLAM incorporates the ORB-based image compression algorithm, which optimizes data transmission with constrained networking resources. We implement and evaluate the Eco-SLAM system in a real environment and demonstrate its effectiveness through extensive experiments ranging from the public SLAM datasets to realistic deployment scenarios. Thorough evaluations show that Eco-SLAM can reduce the memory consumption of other multi-agent SLAM frameworks by up to 20.1% during runtime on the edge server, and save up to 25.1% wireless bandwidth consumption without compromising the accuracy of the map generation.

关键词： Edge Computing Collaborative SLAM Robotics Applications

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Exploring Connections Between Eye Movements and the Big Five Personality Traits

Exploring Connections Between Eye Movements and the Big Five...

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Conference on Human Interface and the Management of Information Thematic Area (HIMI) Held as Part of the 26th International Conference on Human-computer Interaction (HCII)

作者： Tahara, Yuya Inaba, Issei Saito, Yukio Hitomi, Toru Okada, Takuya Honda, Yuka Katura, Takusige Tokyo City Univ Setagaya Ku Tokyo Japan NeU Corp Kanda 2-2Chiyoda Ku Tokyo Japan Toppan Edge Inc Higashi Shinbashi 1-7-3Minato Ku Tokyo Japan

ISBN: (纸本)9783031601132;9783031601149

This study investigates the connection between eye movements, as captured through eye-tracking technology, and personality traits, specifically focusing on the Big Five personality model (Openness, Conscientiousness, Extraversion, Agreeableness, Neuroticism). Utilizing a diverse set of images with clear meanings, such as pictures of animals and landscapes, the research explores how individual personality traits influence visual attention patterns. Participants rated images based on personal preferences while their eye movements were recorded, aiming to correlate these movements with their personality traits. The analysis revealed relationships between certain personality traits and specific aspects of eye movement, such as fixation duration and gaze patterns, suggesting that personality influences how individuals visually engage with content. This has implications for neuro-marketing, educational content tailoring, and enhancing user engagement through personalized visual experiences.

关键词： Eye movement Personality trait Neuromarketing

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A Decision Support System for Cultural and Territorial Infrastructures: A Place-Based and Community-Driven Strategy in Inner Italy 24th

A Decision Support System for Cultural and Territorial Infra...

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24th International Conference on Computational science and Its Applications (ICCSA)

作者： Grieco, Benedetta Somma, Maria Raiola, Maria Lucia Sacco, Sabrina Zizzania, Piero Cerreta, Maria Univ Naples Federico II Dept Architecture DiARC Via Toledo 402 I-80134 Naples Italy

ISBN: (纸本)9783031652844;9783031652851

The study presents a methodological approach, characterized by scalability and replicability, aimed at developing a sustainable territorial strategy, supported by a Collaborative Spatial Decision Support System (CSDSS). The main objective is to elaborate a regeneration process for infrastructure and territorial contexts capable of stimulating situated actions within Inner Italy, where urban revitalisation processes grounded in the concept of community archives could be implemented. The CSDSSis tailored towards a place-based and community-driven strategy for the territory of Atena Lucana, in Southern Italy. It unfolds in three interconnected phases: first, a knowledge phase with a comprehensive understanding of the territory through the integration of various data types;second, an evaluative phase including multi-group analysis supported by the SOCRATES method and multi-criteria analysis employing the integration of QGIS and GeoTopsis methods;third, the data output with the formulation of a suitable strategy for territorial sustainability through collaborative decision-making processes.

关键词： Territorial sustainability SOCRATES method GeoTopsis method

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