检索结果-内蒙古大学图书馆

The influence of fear effect and phase of chaos control of discrete predator–prey system with mixed Holling types

Alexandria engineering Journal 2025年 127卷 296-308页

作者： Madian, A.M. Zheng, Rong El-sheikh, M.M.A. Elettreby, M.F. El-Gaber, A.A. Mathematics and Computer Science Department Faculty of Science Menofia University Menofia Egypt New Engineering Industry College Putian University Fujian Putian351100 China School of Information Engineering Sanming University Fujian Sanming365004 China Mathematics Department Faculty of Science Mansoura University Mansoura35516 Egypt

In this paper, a discrete-time predator–prey system with mixed Holling types I and III functional responses and fear effect is discussed. Three fixed points are determined and their stability is established. Analytical criteria for Neimark Sacker bifurcation (NSB) and flip bifurcation (FB) are proposed. Applying the technique of state feedback control, we introduce the corresponding controlled system. At an unstable fixed point the chaotic orbits can be stabilized. We show that the fear effect of prey species has a negative effect on the density of predator species in our model. Furthermore, fear effect may increase the possibility that prey species will go extinct, which implies that Allee effect may occur in this case. These analytical studies are illustrated with some numerical simulations. © 2025 The Authors

关键词： State feedback

来源：评论

学校读者我要写书评

暂无评论

A new method for promoting the detection of breast cancer in thermograms: applying deep autoencoders for eliminating redundancies in parallel with preserving independent components

引用

Journal of Ambient Intelligence and Humanized Computing 2024年第12期15卷 4085-4099页

作者： Shojaedini, Seyed Vahab Bahramzadeh, Bahram Biomedical Engineering Department Iranian Research Organization for Science & ampTechnology Tehran Iran Department of Computer Engineering Faculty of Engineering Islamic Azad University E-Campus Tehran Iran

Although thermography has been proposed over the past decade as an effective method for breast cancer diagnosis, the complexity of thermograms presents a significant obstacle, making their interpretation challenging. Recently, deep learning has emerged as a promising framework for analyzing breast thermograms. However, the performance of deep neural networks heavily relies on the volume of training images, and the limited number of labeled thermograms necessitates the generation of synthetic images for training. This article introduces a novel method that eliminates redundant or destructive information in synthetic thermograms while preserving essential and independent features using deep autoencoder concepts. Consequently, the proposed strategy enhances the representation of synthetic images for training deep networks, leading to improved breast cancer detection in thermograms. Evaluating the performance of the proposed method on the DMR-IR dataset shows a significant improvement in detecting cancerous breasts in thermograms compared to benchmark methods. Integrating this innovation into the basic model achieved an average accuracy of 92.3%, sensitivity of 93%, and specificity of 91.4%, surpassing the basic model’s 89.1%, 86%, and 92.5%, respectively. The proposed method demonstrated superior performance in mitigating overfitting, as evidenced by a smaller gap between training and validation curves, resulting in a 7% improvement in accuracy and a 3.2% increase in sensitivity. Although there was a slight decrease of 1.1% in specificity, it was outweighed by other parameter improvements. Additionally, the method led to a significant reduction in the dispersion range of test results, approximately six times less than alternative approaches. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

New exact solutions of the Mikhailov-Novikov-Wang equation via three novel techniques

引用

Journal of Ocean engineering and science 2023年第1期8卷 103-110页

作者： Arzu Akbulut Melike Kaplan Mohammed K.A.Kaabar Mathematics-Computer Department Art-Science FacultyEski¸s ehir Osmangazi UniversityEski¸s ehirTurkey Department of Computer Engineering Engineering and Architecture FacultyKastamonu UniversityKastamonuTurkey Institute of Mathematical Sciences Faculty of ScienceUniversity of MalayaKuala Lumpur 50603Malaysia

The current work aims to present abundant families of the exact solutions of Mikhailov-Novikov-Wang equation via three different *** adopted methods are generalized Kudryashov method(GKM),exponential rational function method(ERFM),and modified extended tanh-function method(METFM).Some plots of some presented new solutions are represented to exhibit wave *** results in this work are essential to understand the physical meaning and behavior of the investigated equation that sheds light on the importance of investigating various nonlinear wave phenomena in ocean engineering and *** equation provides new insights to understand the relationship between the integrability and water waves’phenomena.

关键词： Exact solutions Generalized Kudryashov method Modified extended tanh-function method Symbolic computation PDEs

来源：评论

学校读者我要写书评

暂无评论

Kolmogorov Arnold Network for Hyperspectral Image Classification: A Detailed Explanation 2

Kolmogorov Arnold Network for Hyperspectral Image Classifica...

引用

2nd DMIHER International Conference on Artificial Intelligence in Healthcare, Education and Industry, IDICAIEI 2024

作者： Suman, Saurabh Pacharaney, Utkarsha Choudhary, Vishal Kumar Raushan, Rahul Kumar, Abhishek Kumar, Gulshan Faculty of Engineering and Technology Department of Computer Science and Design Maharashtra Wardha India Faculty of Engineering and Technology Department of Artificial Intelligence and Machine Learning Maharashtra Wardha India Faculty of Engineering and Technology Department of Computer Science and Medical Engineering Maharashtra Wardha India

ISBN: (纸本)9798331528713

Hyperspectral imaging (HSI) has been proved to be useful in numerous fields because of its ability to acquire the spectral information across the hundreds of contiguous bands. Nevertheless, the vast dimensionality of the hyperspectral data presents a great problem especially during data processing as well as during classification. Recently, one of the techniques that have attracted most interest for the classification of hyperspectral images is Kolmogorov Arnold Network (KAN), which is efficient with regard to those high-dimensional non- linear data sets found in hyperspectral imagery. This study focuses on how KAN can be utilized for classifying hyperspectral images, how B-spline curves can be used for augmenting the performance of the model, and what experimentation was done with the state-of-the-art hyperspectral data set. From these results, it was established that KAN plus B-spline curves was a good strategy for hyperspectral images classification compared to existing systems in both accuracy and speed. © 2024 IEEE.

关键词： Splines

来源：评论

学校读者我要写书评

暂无评论

Harnessing the Power of CNN-Transformer Encoders in Stress Speech Analysis

Harnessing the Power of CNN-Transformer Encoders in Stress S...

引用

2023 International Conference on Information Technology and Computing, ICITCOM 2023

作者： Shabiyya, Syifa'Hukma Prasetio, Barlian Henryranu Widasari, Edita Rosana Brawijaya University Master of Computer Science Faculty of Computer Science East Java Malang Indonesia Brawijaya University Computer Engineering Faculty of Computer Science East Java Malang Indonesia Brawijaya University Faculty of Computer Science East Java Malang Indonesia

ISBN: (纸本)9798350359633

Stress is the physiological response to mental, emotional, or physical stress, which varies between individuals. A survey by Ipsos Global showed that around 30% of respondents identified stress as a significant health issue. Some countries in Southeast Asia, such as Cambodia, have much higher rates of depression than the world average. In Indonesia, the stress rate reached 9.8% in 2018. This research focuses on Speech Stress Recognition (SSR), an automated method that recognizes stress levels through speech characteristic analysis. We use Mel-Frequency Cepstral Coefficients (MFCC) feature extraction and the CNN-Transformer Encoder model. Evaluation results on the SUSAS dataset showed an overall accuracy of 73.76%. When the classification results are viewed by gender, male data appears better at classifying stress levels than female data. To improve performance, we implemented the Voice Activity Detection method, which resulted in an accuracy of 81% for male and 69.23% for female. The findings of this research have potential applications in various fields, including mental health and emotion analysis in human communication. © 2023 IEEE.

关键词： Speech recognition

来源：评论

学校读者我要写书评

暂无评论

Colossal pattern extraction using optimised length constraints based on differential evolutionary arithmetic optimisation algorithm

引用

International Journal of Information and Communication Technology 2024年第3期24卷 289-304页

作者： Reddy, T. Sreenivasula Sathya, R. Nuka, Mallikharjunarao Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University Annamalai Nagar Tamil Nadu Chidambaram608002 India Department of Computer Science and Engineering Annamalai University Annamalai Nagar Tamil Nadu Chidambaram608002 India Department of Computer Applications Annamacharya Institute of Technology and Sciences YSR Kadapa Andhra Pradesh Rajampet516115 India

Extracting large amounts of information and knowledge from a large database is a trivial task. Existing bulk item mining algorithms for an extensive database are systematic and mathematically expensive and cannot be used for large-scale mining with interruptions. In this paper, the problem of mining the colossal patterns (CPs) is solved by using optimised length constraints (LCs). First, we describe the minimum LC and maximum LC problems and connect them to the optimal LC by identifying the optimal threshold values. Here, the differential evolutionary arithmetic optimisation algorithm (DAOA) is used to find the optimal threshold values of the constraints and extract the colossal patterns. The effectiveness of the proposed algorithm is proven by various experiments using different biological datasets. © 2024 Inderscience Enterprises Ltd.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

Survey of security, performance, and profitability of Monero: a browser-based cryptocurrency

Survey of security, performance, and profitability of Monero...

引用

2023 International Conference on Electrical, computer, Communications and Mechatronics engineering, ICECCME 2023

作者： Pitu, Floarea Gaitan, Nicoleta Cristina Stefan Cel Mare University of Suceava Faculty of Electrical Engineering and Computer Science Suceava Romania Faculty of Electrical Engineering and Computer Science Suceava Romania

ISBN: (纸本)9798350322972

Information is the key to success in every domain;this statement also applies to cryptocurrencies and blockchain domains. Beginning with Bitcoin back in 2009, which the anonymous Japanese Satoshi Nakamoto launched, blockchain technology emerged. This technology has revolutionized and continues to do so in digital transactions. In addition, this technology led to the further development of other cryptocurrencies that are active at these moments on the market. One class of cryptocurrencies obtained differently from classical bitcoin is those obtained due to web-based mining. The most known coins of this type are Monero, Dash, or Electroneum. This paper aims to analyze the web-based mining process of Monero and the whole process's security. In addition, we want to explore the performance of the mining processes used in the user's web browser. Moreover, finally, we aim to research the profitability of coins obtained due to web-browser mining, having as an object of study the cryptocurrency Monero. © 2023 IEEE.

关键词： Bitcoin

来源：评论

学校读者我要写书评

暂无评论

PuzMaty: Supporting Puzzle Mats Design Creation

PuzMaty: Supporting Puzzle Mats Design Creation

引用

2025 IEEE/SICE International Symposium on System Integration, SII 2025

作者： Yamamoto, Sarii Wang, Jiajun Chan, Liwei Sugiura, Yuta Keio University Faculty of Information and Computer Science Kanagawa Japan National Yang Ming Chiao Tung University Department of Computer Science and Engineering Hsinchu Taiwan

ISBN: (纸本)9798331531614

Puzzle mats made of cushioned material are widely used in environments like homes and playrooms to prevent injuries from infants and toddlers falling. The mats feature puzzle-like edges, allowing users to freely adjust their size and shape to fit the space where the mat is placed. This study proposes "PuzMaty,"a design interface for drawing patterns of animals, numbers, letters, etc. using puzzle mats of different colors. This interface is expected to make the puzzle mat function not only as a safety measure but also as an interior decoration. It is also likely to reduce the burden of childcare when placing mats because it makes the number of mats required for a particular space more intuitive. © 2025 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Analysis on Improved Gaussian-Wiener filtering technique and GLCM based Feature Extraction for Breast Cancer Diagnosis 2

Analysis on Improved Gaussian-Wiener filtering technique and...

引用

2nd International Conference on Machine Learning and Data engineering, ICMLDE 2023

作者： Ranjitha, K.V. Pushphavathi, T.P. Department of Computer Science and Engineering Ramaiah University of Applied Sciences Bangalore India Department of Computer Science and Engineering Faculty of Engineering and Technology Ramaiah University of Applied Sciences Bangalore India

Breast cancer is become the most prevailing and fastest growing disease. In medical imaging, the use of machine learning and deep learning algorithms is essential. Classification of the tumor to predict the chemotherapy response for survival is trivial. In this paper, an innovative Gaussian-Wiener filter combination is used for de-noising the MRI images. These pre-processed images with good image quality are selected for tumor detection. On the basis of these pre-processed outputs, important features are extracted to determine the spatial relationship between the image pixels which results in better texture analysis for the tumor images. Analysis is made on the ISPY-2 trial breast MRI database. Results are analyzed which gives better image quality performance for MRI images. The filters and feature extraction method analyzed is used further in the segmentation and optimization process for breast detection and diagnosis to get the best accuracy of nearly 100%. The results also show better texture analysis for extracting features using GLCM based method. Furthermore, the MRI images for these methods used are explained for better performance in the process of breast cancer detection and diagnosis. © 2024 Elsevier B.V.. All rights reserved.

关键词： Feature extraction

来源：评论

学校读者我要写书评

暂无评论

GENERALIZATION AND ESTIMATION ERROR BOUNDS FOR MODEL-BASED NEURAL NETWORKS 11

GENERALIZATION AND ESTIMATION ERROR BOUNDS FOR MODEL-BASED N...

引用

11th International Conference on Learning Representations, ICLR 2023

作者： Shultzman, Avner Azar, Eyar Rodrigues, Miguel R.D. Eldar, Yonina C. Faculty of Mathematics and Computer Science Weizmann Institute of Science Israel Faculty of Engineering Science University College London United Kingdom

Model-based neural networks provide unparalleled performance for various tasks, such as sparse coding and compressed sensing problems. Due to the strong connection with the sensing model, these networks are interpretable and inherit prior structure of the problem. In practice, model-based neural networks exhibit higher generalization capability compared to ReLU neural networks. However, this phenomenon was not addressed theoretically. Here, we leverage complexity measures including the global and local Rademacher complexities, in order to provide upper bounds on the generalization and estimation errors of model-based networks. We show that the generalization abilities of model-based networks for sparse recovery outperform those of regular ReLU networks, and derive practical design rules that allow to construct model-based networks with guaranteed high generalization. We demonstrate through a series of experiments that our theoretical insights shed light on a few behaviours experienced in practice, including the fact that ISTA and ADMM networks exhibit higher generalization abilities (especially for small number of training samples), compared to ReLU networks. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Error analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：