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Exploring the fixed point theory and numerical modeling of fish harvesting system with Allee effect

Modeling Earth Systems and Environment 2025年第4期11卷 1-18页

作者： Yasin, Muhammad Waqas Akhtar, Mobeen Ahmed, Nauman Akgül, Ali Al-Mdallal, Qasem Department of mathematics University of Narowal Narowal Pakistan Department of Mathematics and Statistics The University of Lahore Lahore Pakistan Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Tamilnadu Chennai India Department of Mathematics Art and Science Faculty Siirt University Siirt 56100 Turkey Department of Mathematics Mathematics Research Center Near East University Near East Boulevard Nicosia 99138 Turkey Department of Computer Engineering Biruni University Istanbul Topkapi 34010 Turkey Department of Mathematical Sciences UAE University P.O. Box 17551 Al Ain United Arab Emirates

Fish harvesting has a major role in nutritive food that is easily accessible for human nourishment. In this article, a reaction-diffusion fish harvesting model with the Allee effect is analyzed. The study of population models is a need of this hour because by using precautionary measures, mankind can handle the issue of food better. The basic mathematical properties are studied such as equilibrium analysis, stability, and consistency of this model. The Implicit finite difference and backward Euler methods are used for the computational results of the underlying model. The linear analysis of both schemes is derived and schemes are unconditionally stable. By using the Taylor series consistency of both schemes is proved. The positivity of the Implicit finite difference scheme is proved by using the induction technique. A test problem has been used for the numerical results. For the various values of the parameters, the simulations are drawn. The dynamical properties of continuous models, like positivity, are absent from the simulations produced by the backward Euler scheme. Implicit finite difference scheme preserves the dynamical properties of the model such as positivity, consistency, and stability. Simulations of the test problem prove the effectiveness of the Implicit finite difference scheme. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Allee effect Analysis Backward Euler scheme Holling type II Implicit finite difference scheme Reaction-diffusion model Simulations

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Sampled-data local exponential stabilization of nonlinear retarded systems by first order approximation methods and spline interpolation of measures 63

Sampled-data local exponential stabilization of nonlinear re...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Pepe, P. Borri, A. Di Ferdinando, M. University of l'Aquila Center of Excellence for Research Dews Department of Information Engineering Computer Science and Mathematics L'Aquila67100 Italy Istituto di Analisi Dei Sistemi Ed Informatica 'A. Ruberti' Consiglio Nazionale Delle Ricerche Rome00185 Italy

ISBN: (纸本)9798350316339

It is proved, for systems described by nonlinear retarded functional differential equations, that (local) exponential stability is guaranteed under fast sampling and spline approximation of stabilizing feedbacks obtained in continuous-time by first-order approximation methods. At the (high) price to consider just the local case, here we make rid of any kind of assumptions such as: the availability and exhibition of Lyapunov-Krasovskii functionals with suitable properties;the availability and exhibition of suitable steepest descent feedbacks of the state with suitable properties;global Lipschitz properties of the function describing the dynamics and of the state feedback. No assumptions are introduced besides standard Fréchet differentiability at the origin of the function describing the dynamics, and the availability of a linear state feedback for the stabilization of the first order approximating linear system, which a huge literature is devoted to with so many results. © 2024 IEEE.

关键词： Continuous time systems

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Report-Guided Cross-Modal Representation Learning for Predicting EGFR Mutations by Whole Slide Image

Report-Guided Cross-Modal Representation Learning for Predic...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Qiao, Qi Shi, Jun Jiang, Zhiguo Wang, Wei Wu, Haibo Zheng, Yushan Hefei University of Technology School of Computer Science and Information Engineering Hefei230601 China Hefei University of Technology School of Software Hefei230601 China Beihang University Image Processing Center School of Astronautics Beijing102206 China University of Science and Technology of China Division of Life Sciences and Medicine Department of Pathology First Affiliated Hospital of Ustc Hefei230036 China University of Science and Technology of China Intelligent Pathology Institute Division of Life Sciences and Medicine Hefei230036 China Beihang University School of Engineering Medicine Beijing Advanced Innovation Center for Biomedical Engineering Beijing100191 China

ISBN: (纸本)9798350386226

Traditional PCR/NGS-based multigene panel testing is time-consuming and costly. Predicting EGFR mutations directly from H&E stained whole slide images (WSIs) can alleviate these limitations. Furthermore, histopathological reports contain valuable textual information that correlates with tissue areas in WSIs. However, recent research mainly analyses EGFR mutation status only from a single modality, ignoring rich information contained in reports. In this paper, we propose a report-guided cross-modal representation learning method for predicting EGFR mutations by WSIs. Specifically, we reconstruct report-level embeddings through exploring intrinsic relationships between diagnostic words in histopathological reports and tissue areas in WSIs. Finally, reconstructed histopathological report embedding and aggregated WSI embedding are fused for final prediction. More importantly, molecular testing report is also introduced as prior supervision information at the training stage to guarantee semantic consistency of fused feature and molecular report embedding. We evaluate our method on the TCGA-EGFR public benchmark dataset and an in-house clinical dataset (USTC-EGFR). Experimental results demonstrate that our method outperforms existing approaches in EGFR mutation prediction, highlighting the benefits of cross-modal learning in enhancing feature representational ability. The code is available at https://***/HFUT-miaLab/RCRL. © 2024 IEEE.

关键词： Supervised learning

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Real-time optimization of 5G based on MIMO detection algorithm 5

Real-time optimization of 5G based on MIMO detection algorit...

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5th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2023

作者： Jin, Jin Jin, Dongshuai Zheng, Hui Wang, Yifan Zhang, Guoquan Zhang, Shenguo Wang, Shuzhi Northwest Minzu University College of Electrical Engineering Lanzhou China Northwest Minzu University Gansu Engineering Research Center for Eco-Environmental Intelligent Networking College of Electrical Engineering Lanzhou China Northwest Minzu University College of Mathematics and Computer Science Lanzhou China

ISBN: (纸本)9798350310603

Multiple Input Multiple Output (MIMO) application is a key technology for 5G, which can improve the spectrum efficiency greatly, channel capacity and data transmission efficiency of the system without increasing the Output power and system *** detection algorithm is a key application in *** communication quality of system is determined by the performance of sampling module *** this article, the Zero Forcing (ZF) sampling algorithm and Minimum Mean Square Error (MMSE) sampling algorithm are compared by MATLAB firstly, and the conclusion that the MMSE sampling algorithm may have better performance is ***, the C program implementation process of MMSE sampling algorithm is designed, and the 256-bit Intel single-instruction multi-data instruction set is used for algorithm optimization based on its C program, in order to realize the real-time optimization of MIMO sampling algorithm. © 2023 IEEE.

关键词： Mean square error

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Attendance System via Internet of Things, Blockchain and Artificial Intelligence Technology: Literature Review 37th

Attendance System via Internet of Things, Blockchain and Art...

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37th International Conference on advanced Information Networking and Applications, AINA 2023

作者： Abidemi, Sarumi Usman Mubarak, Auwalu Saleh Akanni, Olukayode Ameen, Zubaida Said Cacciagrano, Diletta Al-turjman, Fadi Artifiical Intelligence Engineering Department AI and Robotics Institue Near East University Mersin 10 Nicosia Turkey Computer Science Division School of Science and Technology Camerino University Camerino62032 Italy Research Center for AI and IoT Faculty of Engineering University of Kyrenia Mersin 10 Kyrenia Turkey

ISBN: (纸本)9783031286933

Many researchers have make efforts on creating several attendance systems to keep track of student attendance in school which is also part of academic curriculum that will have great impact in student academic performance. There have been different technologies such as RFID, face recognition, biometric, web-based attendance system etc. To capture attendance in a way that’s better than the traditional method of pen and paper or roll call system. Making this attendance record available on blockchain network and applying artificial intelligence algorithm for prediction or classification in correlation with the data captured from student attendance purpose. Several articles, papers and journals has been reviewed from different research plethora of research publishers’ database through internet such as Google scholar, IEEExplore, Springerslink etc. This will make it easy for comparing several attendance systems with respect to internet of things, blockchain and artificial intelligence to address the research gap in this aspect. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Blockchain

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DecGAN: Decoupling Generative Adversarial Network for Detecting Abnormal Neural Circuits in Alzheimer's Disease

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 5050-5063页

作者： Pan, Junren Zuo, Qiankun Wang, Bingchuan Chen, C.L. Philip Lei, Baiying Wang, Shuqiang Chinese Academy of Sciences Shenzhen Institutes of Advanced Technology Shenzhen518055 China Hubei University of Economics Hubei Key Laboratory of Digital Finance Innovation School of Information Engineering Hubei Internet Finance Information Engineering Technology Research Center Hubei Wuhan430205 China Central South University School of Automation Changsha410083 China South China University of Technology School of Computer Science and Engineering Guangzhou510641 China Shenzhen University School of Biomedical Engineering Shenzhen518060 China

One of the main reasons for Alzheimer's disease (AD) is the disorder of some neural circuits. Existing methods for AD prediction have achieved great success, however, detecting abnormal neural circuits from the perspective of brain networks is still a big challenge. In this work, a novel decoupling generative adversarial network (DecGAN) is proposed to detect abnormal neural circuits for AD. Concretely, a decoupling module is designed to decompose a brain network into two parts: one part is composed of a few sparse graphs that represent the neural circuits largely determining the development of AD;the other part is a supplement graph, whose influence on AD can be ignored. Furthermore, the adversarial strategy is utilized to guide the decoupling module to extract the feature more related to AD. Meanwhile, by encoding the detected neural circuits to hypergraph data, an analytic module associated with the hyperedge neurons algorithm is designed to identify the neural circuits. More importantly, a novel sparse capacity loss based on the spatial-spectral hypergraph similarity is developed to minimize the intrinsic topological distribution of neural circuits, which can significantly improve the accuracy and robustness of the proposed model. Experimental results demonstrate that the proposed model can effectively detect the abnormal neural circuits at different stages of AD, which is helpful for pathological study and early treatment. © 2020 IEEE.

关键词： Brain

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CPU Execution Time Analysis based on RISC-V ISA Simulators: A Survey 16

CPU Execution Time Analysis based on RISC-V ISA Simulators: ...

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16th International Conference on Development and Application Systems, DAS 2022

作者： Iuga, Nicolai Zagan, Ionel Gaitan, Vasile Gheorghita Stefan cel Mare University Faculty of Electrical Engineering and Computer Science Suceava Romania Integrated Center for Research Development and Innovation in Advanced Materials Suceava Romania

ISBN: (纸本)9781665481625

Multiple components affect the behavior of CPU execution tasks, mainly mutual exclusion during access to the shared resources and synchronous transmissions between tasks that require specific priorities. Referring to real-time task scheduling, the most important issues addressed are monitoring the deadline of the tasks, the probability of non-compliance with the deadline and ensuring that they are completed within the deadline imposed by the controlled system. This leads to the fact that a tasks set is feasible if the system has adequate resources to execute the tasks without losing any deadlines. To approach this challenge, this article addresses the feasibility analysis of runtime for real-time tasks to be performed in a virtual space before applying to a real embedded device. These processes take place offline, even before a system executes a set of tasks. In order to perform the feasibility analysis of the system, efforts are being made to provide virtual environments and simulators, such as the RISC-V ISA simulator and the WCET (Worst Case Execution Time) measurement, subsequently. These simulators have application-specific requirements, with their own advantages. © 2022 IEEE.

关键词： Simulators

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Tackling the Qubit Mapping Problem with Permutation-Aware Synthesis

Tackling the Qubit Mapping Problem with Permutation-Aware Sy...

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Quantum Computing and engineering (QCE), IEEE International Conference on

作者： Ji Liu Ed Younis Mathias Weiden Paul Hovland John Kubiatowicz Costin Iancu Mathematics and Computer Science Division Argonne National Laboratory Computational Research Division Lawrence Berkeley National Laboratory Department of Electrical Engineering and Computer Science University of California Berkeley

We propose a scalable, hierarchical qubit mapping and routing algorithm that harnesses the power of circuit synthesis. First, we decompose large circuits into subcircuits small enough to be directly resynthesized. For each block, we pre-synthesize them for all permutations of its input and output qubits. Following this offline step, we employ a permutation-aware, block-based generalization of the popular SABRE mapping algorithm. This mapping step stitches together blocks by choosing an input-output permutation that minimizes intrablock gate count and required inter-block communication (SWAP and bridge gates). Our approach has a twofold advantage: 1) circuit synthesis may eliminate more two-qubit gates than other optimizing compilers; 2) considering all permutations of input and output qubits eliminates communication operations transparently. In contrast, other mapping algorithms can only introduce communication operations. We show that we can produce better-quality circuits than commercial compilers: shorter by up to 68% (18% on average) fewer gates than Qiskit, up to 36% (9% on average) fewer gates than Tket. We outperform BQSkit, a permutation-unaware, synthesis-based compiler, by up to 67% (21% on average) fewer gates. We also exceed experimental optimal mappers such as OLSQ in quality (10.7% shorter circuits) and time to solution. Our scalable, heuristic approach can be seamlessly integrated into any quantum circuit compiler or optimization infrastructure, and it applies well to any qubit technology, such as superconducting and trapped ions.

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A conceptional structure for challenging the rebound effect of the product-service system 33

A conceptional structure for challenging the rebound effect ...

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33rd CIRP Design Conference

作者： Alfarisi, Salman Mitake, Yuya Tsutsui, Yusuke Wang, Hanfei Shimomura, Yoshiki Faculty of Systems Design Tokyo Metropolitan University Tokyo191-0065 Japan Human Augmentation Research Center National Institute of Advanced Industrial Science and Technology Chiba277-0882 Japan Faculty of Computer Science and Systems Engineering Okayama Prefectural University 719-1197 Japan

The product obsolescence rate is one of the product-service system rebound effect issues. Obsolescence can be generated by both planned obsolescence and post-production obsolescence. Planned obsolescence can increase sales and revenue artificially. However, the pattern of planned obsolescence has demonstrated that obsolescence is no longer limited to functional obsolescence but rather rapidly evolves to include quality and aesthetic aspects. Moreover, post-production consuming behaviours hasten the rate of product obsolescence, especially in the absence of ownership. At this point, rapid obsolescence contradicts the spirit of the Product-service System's (PSS) value proposition. During the stage of value co-creation, such topics must be considered. According to research on PSS and the co-creation process, the co-creation of value is inherent to PSS. Nevertheless, managing the process of value co-creation is another challenge. In addition, decision-making should also be prevented from being dominated by a high degree of centralisation. This paper presents a preliminary investigation into constructing a framework for managing the value co-creation process and decision-making to prevent the rebound effect based on conceptual review. This study identifies methods applicable to the co-creation procedure. A conceptional structure of co-creation of value and decision-making is presented. © 2023 The Authors. Published by Elsevier B.V.

关键词： Obsolescence

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Efficient Distributed Sequence Parallelism for Transformer-based Image Segmentation

Efficient Distributed Sequence Parallelism for Transformer-b...

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IS and T International Symposium on Electronic Imaging 2024: High Performance Computing for Imaging 2024

作者： Lyngaas, Isaac Meena, Murali Gopalakrishnan Calabrese, Evan Wahib, Mohamed Chen, Peng Igarashi, Jun Huo, Yuankai Wang, Xiao National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN United States Department of Radiology Duke University DurhamNC United States Riken Center for Computational Science Tokyo Japan National Institute of Advanced Industrial Science and Technology Tokyo Japan Department of Computer Science Vanderbilt University NashvilleTN United States

We introduce an efficient distributed sequence parallel approach for training transformer-based deep learning image segmentation models. The neural network models are comprised of a combination of a Vision Transformer encoder with a convolutional decoder to provide image segmentation mappings. The utility of the distributed sequence parallel approach is especially useful in cases where the tokenized embedding representation of image data are too large to fit into standard computing hardware memory. To demonstrate the performance and characteristics of our models trained in sequence parallel fashion compared to standard models, we evaluate our approach using a 3D MRI brain tumor segmentation dataset. We show that training with a sequence parallel approach can match standard sequential model training in terms of convergence. Furthermore, we show that our sequence parallel approach has the capability to support training of models that would not be possible on standard computing resources. © 2024, Society for Imaging science and Technology.

关键词： Image segmentation

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