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arXiv 2022年

作者： Fitzsimmons, Zack Hemaspaandra, Edith Dept. of Math. and Computer Science College of the Holy Cross WorcesterMA01610 United States Department of Computer Science Rochester Institute of Technology RochesterNY14623 United States

The first step in classifying the complexity of an NP problem is typically showing the problem in P or NP-complete. This has been a successful first step for many problems, including voting problems. However, in this paper we show that this may not always be the best first step. We consider the problem of constructive control by replacing voters (CCRV) introduced by Loreggia et al. (2015) for the scoring rule First-Last, which is defined by (1, 0, ⋯;0, -1). We show that this problem is equivalent to Exact Perfect Bipartite Matching, and so CCRV for First-Last can be determined in random polynomial time. So on the one hand, if CCRV for First-Last is NP-complete then RP = NP, which is extremely unlikely. On the other hand, showing that CCRV for First-Last is in P would also show that Exact Perfect Bipartite Matching is in P, which would solve a well-studied 40-year-old open problem. By considering RP as an option we also gain insight into the complexity of CCRV for 2-Approval, ultimately showing it in P, which settles the complexity of the sole open problem in the comprehensive table from Erdélyi et al. (2021). Copyright © 2022, The Authors. All rights reserved.

关键词： Polynomial approximation

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On mixing properties of Markov tree-shifts

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Topology and its Applications 2024年 346卷

作者： Ban, Jung-Chao Chang, Chih-Hung Huang, Nai-Zhu Lai, Guan-Yu Department of Mathematical Sciences National Chengchi University Taipei 11605 Taiwan Math. Division National Center for Theoretical Science National Taiwan University Taipei 10617 Taiwan Department of Applied Mathematics National University of Kaohsiung Kaohsiung 81148 Taiwan

In this article, we characterize the various kinds of mixing properties, in the sense of classical and complete prefix code (CPC for short) considerations, of the axial product of Z-shifts on a free semigroup G. Axial product space is an anisotropic Markov system which plays an essential role in the research of statistical physics. We reveal matrix criteria for examining these properties. Furthermore, the existence of dense (CPC-)periodic points is also demonstrated. Combining this with the aforementioned results of the (CPC-)mixing properties exhibits whether a referred system is CPC-chaotic in the sense of Devaney. © 2024 Elsevier B.V.

关键词： Dense (CPC-)periodic points Markov tree-SFTs Mixing property

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A New Clustering Approach based on Trust and Rat Swarm Algorithm for WSN Applications

A New Clustering Approach based on Trust and Rat Swarm Algor...

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Advances in Intelligent Computing and Applications (AICAPS), International Conference on

作者： Walid Osamy Ahmed Salim Amel Al Ali Ahmed M. Khedr Computer Science Department Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Math. Department Faculty of Science Zagazig University Zagazig Egypt Department of CS College of Sci. and Arts Al-Methnab Qassim University KSA Dept. of Information Systems Sharjah University Sharjah UAE Dept. of Computer Science Sharjah University Sharjah UAE

In this paper, a clustering approach called CATRSO is proposed. The selection of cluster heads (CH) is performed by considering the trust value of the nodes in order to select the most trustworthy nodes as CH and Rat Swarm Optimizer is employed for CH selection process. The trust value of the nodes and remaining energy are taken into account while designing the fitness function. In addition, a chain routing approach is employed between CHs for energy savings. The results demonstrate that the CATRSO technique is successful in selecting the most trustworthy nodes as CH and outperforms earlier efforts in the literature in terms of energy efficiency, average network lifetime, and trustworthiness of selected CHs.

关键词： Wireless communication Measurement Wireless sensor networks Simulation Clustering algorithms Rats Routing

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Collaborative Control of Aerial Robots for Inferring Human Intent from Gaze Following

Collaborative Control of Aerial Robots for Inferring Human I...

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Control Technology and Applications (CCTA),

作者： Vishnu S. Chipade Alia Gilbert Daniel Harari Dimitra Panagou Department of Aerospace Engineering University of Michigan Ann Arbor MI USA Department of Robotics University of Michigan Ann Arbor MI USA Department of Computer Science and Applied Math Weizmann AI Center Weizmann Institute of Science Israel

In an ideal human-robot collaboration, autonomous robots work side-by-side with humans in a joint workspace, often performing complementary tasks to the humans. A robotic ability to infer human intention and goals directly from human behavior will facilitate the collaboration and maximize its efficiency. In this paper, we focus on inferring which object the human wants picked up next, based on what the human is looking at, by visually following the human gaze and head orientation. We develop a coordination protocol for a team of aerial robots to extract effective human head and gaze cues. The aerial robots are controlled to navigate around the human and collect data that improves the detection of the human's gaze and hence the intended object to be picked up. The effectiveness of the approach is shown using simulations in AirSim, a photo-realistic simulator.

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Retraction Note: An efficient quantum based D2D computation and communication approach for the internet of things

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Optical and Quantum Electronics 2024年第11期56卷 1-2页

作者： Mekala, M. S. Srivastava, Gautam Chun-Wei Lin, Jerry Dhiman, Gaurav Park, Ju H. Jung, Ho-Youl Department of Information and Communication Engineering Yeungnam University Gyeongsan Korea RLRC for Autonomous Vehicle Parts and Materials Innovation Yeungnam University Gyeongsan Korea Department of Math and Computer Science Brandon University Brandon Canada Western Norway University of Applied Sciences Gaurav Dhiman Bergen Norway Department of Computer Science Government Bikram College of Commerce Patiala India Department of Electrical Engineering Yeungnam University Gyeongsan Korea Research Centre for Interneural Computing China Medical University Taichung Taiwan University Centre for Research and Development Department of Computer Science and Engineering Chandigarh University Gharuan India Department of Computer Science and Engineering Graphic Era Deemed to be University Dehradun India

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Enhancing Industrial Productivity through AI-Driven Systematic Literature Reviews 19

Enhancing Industrial Productivity through AI-Driven Systemat...

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19th International Conference on Web Information Systems and Technologies, WEBIST 2023

作者： Coelho, Jaqueline Gutierri Bispo, Guilherme Dantas Vergara, Guilherme Fay Saiki, Gabriela Mayumi Serrano, André Luiz Marques Weigang, Li Neumann, Clovis Martins, Patricia Helena de Oliveira, Welber Santos Albarello, Angela Brigida Casonatto, Ricardo Accorsi Missel, Patrícia de Medeiros Junior, Roberto de Oliveira Gomes, Jefferson Rosano-Peña, Carlos da Costa, Caroline Cabral F. Latitude Decision Making Technologies Lab University of Brasilia Campus Darcy Ribeiro Brasilia Brazil Projectum Research Group for Math. Methodologies Applied to Management University of Brasilia Brasilia Brazil SENAI National Service of Industrial Learning Federal District Brazil Department of Production Engineering Faculty of Technology University of Brasília Federal District Brazil Department of Computer Science University of Brasilia Federal District Brazil Department of Economics University of Brasília Federal District Brazil UNITEC Innovation and Technology Unit National Service of Industrial Learning Federal District Brazil Department of Electrical University of Brasilia Federal District Brazil Department of Administration University of Brasilia Federal District Brazil

ISBN: (纸本)9789897586729

The advent of Artificial Intelligence (AI) has opened up new possibilities for improving productivity in various industry sectors. In this paper, we propose a novel framework aimed at optimizing systematic literature reviews (SLRs) for industrial productivity. By combining traditional keyword selection methods with AI-driven classification techniques, we streamline the review process, making it more efficient. Leveraging advanced natural language processing (NLP) approaches, we identify six key sectors for optimization, thereby reducing workload in less relevant areas and enhancing the efficiency of SLRs. This approach helps conserve valuable time and resources in scientific research. Additionally, we implemented four machine learning models for category classification, achieving an impressive accuracy rate of over 75%. The results of our analyses demonstrate a promising pathway for future automation and refinements to boost productivity in the industry. Copyright © 2023 by SCITEPRESS - science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)

关键词： Natural language processing systems

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Reduced basis method with parameterized boundary conditions for room acoustics 51

Reduced basis method with parameterized boundary conditions ...

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51st International Congress and Exposition on Noise Control Engineering, Internoise 2022

作者： Llopis, Hermes Sampedro Engsig-Karup, Allan P. Jeong, Cheol-Ho Pind, Finnur Hesthaven, Jan S. Rambøll Denmark Hannemanns Allé 53 Copenhagen2300 Denmark Department of Applied Mathematics and Computer Science Technical University of Denmark Matematiktorvet 303b/r108 Kongens Lyngby2800 Denmark Acoustic Technology Department of Electrical and Photonics Engineering Technical University of Denmark Ørsteds Plads 352 Kongens Lyngby2800 Denmark Treble Technologies Bjargargata 1 Reykjavik102 Iceland Comp. Math. and Simulation Science Ecole polytechnique federale de Lausanne Rte Cantonale Lausanne1015 Switzerland

ISBN: (纸本)9781906913427

Room acoustic simulations can be performed by means of numerical methods, which typically solve the wave equation in an enclosure through discretization techniques. These methods provide high-fidelity solvers that include all the wave phenomena but are computationally costly. This paper investigates the potential of a reduced basis method for simulating room acoustics when the boundary properties are changed iteratively, e.g., for the investigation of effects of design changes in rooms where different boundary properties are simulated. Such studies increase the computational cost when using traditional high-fidelity solvers. The presented framework allows reducing the computational burden by applying reduced basis methods and solving the problem in a low-dimensional subspace where the absorption properties of complex boundary conditions are parameterized, e.g., the thickness of a porous material. The potential of the proposed framework is analyzed in terms of computational efficiency, accuracy and storage requirements. A computational speedup of two orders of magnitude is demonstated for a 2D case with an upper frequency of 2 kHz, and impressive three orders of magnitude for a 3D case with an upper frequency of 1 kHz showing a potential of having an increase in terms of speedup when increasing the size of the domain. The storage requirement for a 2D case with an upper frequency of 8 kHz is 10.8GB while for a 3D case with an upper frequency of 1 kHz is 8 GB. © 2022 Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. All rights reserved.

关键词： Boundary conditions

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Hydrodynamic Studies of Underground Gas Storages 13

Hydrodynamic Studies of Underground Gas Storages

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13th International Conference on Advanced computer Information Technologies, ACIT 2023

作者： Pyanylo, Yaroslav Prytula, Zoia Prytula, Myroslav Hymko, Olha Prytula, Nazar Pyanylo, Halyna Pidstryhach Institute for Applied Problems of Mechanics and Mathematics National Academy of Sciences of Ukraine Department of Mathematical Modeling of Transfer Processes in Distributed Systems Lviv Ukraine Pidstryhach Inst. for Appl. Prob. of Mechanics and Math. National Academy of Sciences of Ukraine Laboratory of Mathematical Problems of Mechanics of Inhomogeneous Bodies Lviv Ukraine Research and Design Institute of Gas Transport of PJSC 'Ukrtransgaz' Department of Development of Systems for Optimal Planning and Forecasting of UGS Operating Modes Lviv Ukraine Lviv Polytechnic National University Department of Automation and Computer-Integrated Technologies Lviv Ukraine

Problems of research of underground gas storage (UGS) wells are given. The analysis of the results of well research is carried out and the constant variability of filtration resistance coefficients of bottomhole zones of wells is substantiated. Studies of the influence of bottomhole pressures of wells on the calculated pressure at gas gathering stations (GGS) of underground storage facilities have been carried out. It was found that the calculated filtration resistance coefficients do not allow to calculate the pressures at the gas gathering stations of the underground storage plant with sufficient accuracy. The magnitude of the discrepancy between the measured and calculated pressures on the GGS varies depending on the flow rate and operating time of wells. It is established that the calculation of depression (repression) of pressure in the bottomhole zones of wells in non-stationary conditions of their operation gives underestimated results. © 2023 IEEE.

关键词： Hydrodynamics

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Poster: Selection of Optimal Neural Model using Spiking Neural Network for Edge Computing*

Poster: Selection of Optimal Neural Model using Spiking Neur...

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International Conference on Distributed Computing Systems

作者： Sanaullah Kaushik Roy Ulrich Ruckert Thorsten Jungeblut Dep. of Eng. and Math. Industrial IOT University of Applied Sciences and Arts Bielefeld Germany Dep. of Computer Science Cyber Defense and AI Lab Lab North Carolina A&T State University NC USA Dep. of Faculty of Technology Cognitive Interaction Technology Universitat Bielefeld Bielefeld Germany

ISBN: (数字)9798350386059

ISBN: (纸本)9798350386066

Spiking Neural Networks (SNNs), are inspired by the biological brain's complicated signaling mechanisms and possess unique characteristics that set them apart from traditional artificial neural networks. This research study explores the challenging domain of image classification, specifically utilizing the well-known MNIST dataset through the development and thorough evaluation of different neural models for edge computing. However, the primary contribution is the autonomous selection of the best-performing SNN model through various early stopping approaches and validation functions, allowing the models to autonomously adapt during training. In addition, this article presents the standalone AutoML-SNN model, which is the introduction of dynamic elements into selected SNN domains, enhancing their adaptability to complex patterns within the dataset. Furthermore, the early stopping methodologies are used to reduce overfitting hazards, and using the 3000-neuron set, the LIF appeared as the most proficient neural model.

关键词： Training Adaptation models Computational modeling Biological system modeling Neurons Spiking neural networks Hazards

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SIMAP: A simplicial-map layer for neural networks

arXiv

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arXiv 2024年

作者： Gonzalez-Diaz, Rocio Gutiérrez-Naranjo, Miguel A. Paluzo-Hidalgo, Eduardo The Department of Applied Math I School of Engineering University of Sevilla Seville Spain The Department of Computer Science and Artificial Intelligence School of Engineering University of Sevilla Seville Spain The Department of Quantitative Methods Universidad Loyola Andalucía Campus Sevilla Dos Hermanas Seville Spain

In this paper, we present SIMAP, a novel layer integrated into deep learning models, aimed at enhancing the interpretability of the output. The SIMAP layer is an enhanced version of Simplicial-Map Neural Networks (SMNNs), an explainable neural network based on support sets and simplicial maps (functions used in topology to transform shapes while preserving their structural connectivity). The novelty of the methodology proposed in this paper is two-fold: Firstly, SIMAP layers work in combination with other deep learning architectures as an interpretable layer substituting classic dense final layers. Secondly, unlike SMNNs, the support set is based on a fixed maximal simplex, the barycentric subdivision being efficiently computed with a matrix-based multiplication algorithm. © 2024, CC BY.

关键词： Deep learning

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