检索结果-内蒙古大学图书馆

Changes in lake surface temperature on the Tibetan Plateau from 2000 to 2022 and their driving factors

Science China Earth Sciences 2025年第5期68卷 1641-1655页

作者： Yuanlin QIU Jie CHEN Deliang CHEN State Key Laboratory of Water Resources Engineering and Management Wuhan University Department of Earth System Sciences Tsinghua University Regional Climate Group Department of Earth Sciences University of Gothenburg

Lake surface temperature（LST） is a key parameter in regulating regional water-carbon cycles and biological processes, playing a critical role in the energy and mass balance of lakes. The Tibetan Plateau（TP） is home to thousands of lakes and is highly sensitive to climate change. Therefore, the response of these lakes to a warming climate is crucial for the water security and ecological stability of the “Asian Water Tower”. However, the long-term trend of LST and its driving factors on the TP over the past two decades remain unclear. Here, we employ an all-weather land surface temperature dataset and a representative lake method to investigate the interannual trend of LST on the TP from 2000 to 2022. The analysis uses temperature data from 519 to 581 lakes with interannual dynamic changes in surface area. The results show that lakes on the TP exhibit an overall warming trend, with an average rate of 0.10±0.27°C（10 a）-1. Among the representative lakes, 61% show a warming trend. The most significant warming occurs in autumn, with 91% of the representative lakes showing an increase in LST(0.47±0.30°C（10 a）-1). The warming rate in spring is about half of that in autumn. In winter, the LST trend exhibits a polarized pattern: although some lakes experience significant warming, more than half show intense cooling. In summer, the trend of LST change is more moderate than that in other seasons. The positive feedback from the reduction in lake ice duration drives the LST trend on the TP. The lake ice duration reduces every 10-day, the annual LST increases 0.4°***, altitude and lake expansion can also influence LST changes. Lakes at lower altitudes generally experience higher warming trends. Lake expansion can exacerbate lake warming in autumn by enhancing thermal inertia and delaying lake freeze-up.

关键词： Tibetan Plateau Lake surface temperature Climate change Random forest Attribution analysis

来源：评论

学校读者我要写书评

暂无评论

An Uncertainty Quantization-Based Method for Anti-UAV Detection in Infrared Images

引用

Computers, Materials & Continua 2025年第4期83卷 1439-1458页

作者： Can Wu Wenyi Tang Yunbo Rao Yinjie Chen Hui Ding Shuzhen Zhu Yuanyuan Wang School of Information and Software Engineering University of Electronic Science and Technology of ChinaChengdu610054China State Key Laboratory of Air Traffic Management System Nanjing210000China National Airspace Management Center Beijing100094China

Infrared unmanned aerial vehicle(UAV)target detection presents significant challenges due to the inter-play between small targets and complex *** methods,while effective in controlled environments,often fail in scenarios involving long-range targets,high noise levels,or intricate backgrounds,highlighting the need for more robust *** address these challenges,we propose a novel three-stage UAV segmentation framework that leverages uncertainty quantification to enhance target *** framework incorporates a Bayesian convolutional neural network capable of generating both segmentation maps and probabilistic uncertainty *** utilizing uncer-tainty predictions,our method refines segmentation outcomes,achieving superior detection ***,this marks the first application of uncertainty modeling within the context of infrared UAV target *** evaluations on three publicly available infrared UAV datasets demonstrate the effectiveness of the proposed *** results reveal significant improvements in both detection precision and robustness when compared to state-of-the-art deep learning *** approach also extends the capabilities of encoder-decoder convolutional neural networks by introducing uncertainty modeling,enabling the network to better handle the challenges posed by small targets and complex environmental *** bridging the gap between theoretical uncertainty modeling and practical detection tasks,our work offers a new perspective on enhancing model interpretability and *** codes of this work are available openly at https://***/general-learner/UQ_Anti_UAV(acceessed on 11 November 2024).

关键词： Object segmentation uncertainty quantification bayesian convolutional neural network

来源：评论

学校读者我要写书评

暂无评论

Joint sequential decision of maintenance and spare parts inventory for multi-unit repairable systems

引用

International Journal of Reliability and Safety 2025年第1期19卷 22-59页

作者： Zhang, Xiaohong Li, Yuxin Zhang, Jianfei Gan, Jie Zhang, Yongfei Shen, Juan Division of Industrial and System Engineering School of Economics & Management Taiyuan University of Science & Technology Shanxi Province Taiyuan China School of Economics & Management Taiyuan University of Science & Technology Shanxi Province Taiyuan China

Joint decision-making for preventive maintenance and spare parts inventory in multi-component systems is crucial for industrial applications, especially as many expensive, complex equipments can be repaired and reused. This study investigates this joint decision-making using a discrete multi-state degradation model, focusing on the unique characteristics of repairable systems, including their structure and maintenance strategies. First, the operational interactions among production, maintenance, and inventory are analysed to derive state transition probability models for degradation and ordering processes. Subsequently, a sequential decision model is developed to minimise the total system cost, identifying preventive maintenance thresholds, inspection periods, and order batch sequences. To address the problem, a combination of global dynamic programming and genetic algorithms is employed. Numerical experiments with wind turbine spindles validate the decision model, demonstrating its effectiveness in addressing maintenance and inventory optimisation in repairable multi-unit systems while ensuring an optimal dynamic combination of decision variables. Copyright © 2025 Inderscience Enterprises Ltd.

关键词： Wind turbines

来源：评论

学校读者我要写书评

暂无评论

Patch-based Histopathological Images for Non- Hodgkin Lymphoma Detection using Voting CNN with Layer Freezing

IAENG International Journal of Computer Science

引用

IAENG International Journal of Computer Science 2025年第4期52卷 1222-1234页

作者： Luthfiarta, Ardytha Dewi, Ika Novita Hidayat, Erwin Yudi Supriyanto, Catur Putra, Permana Langgeng Wicaksono Ellwid Yousif, Ahmed Sabeeh Department of Informatics Engineering Universitas Dian Nuswantoro Indonesia Department of Information System Universitas Dian Nuswantoro Indonesia Technical College of Management Mousl Northern Technical University Iraq

Non-Hodgkin Lymphoma (NHL) is characterized by its diverse subtypes of lymphoid malignancies, presenting challenges for accurate diagnosis due to the variability in tissue morphology and immunophenotypic profiles. This research proposes a novel automated approach for NHL subtype classification using histopathological images, integrating a combination of patch-based analysis with a voting ensemble of Convolutional Neural Networks (CNN). Pre-trained CNN models such as DenseNet169, MobileNetV2, and NASNetMobile were enhanced using a layer-freezing technique to preserve learned low-level features while fine-tuning higher-level layers for improved specificity in NHL detection. A majority voting mechanism aggregates predictions from individual image patches, enhancing classification robustness. The proposed model was evaluated on the IICBU 2008 Lymphoma image dataset, achieving a classification accuracy of 99.11% and an F1- score of 99.11%, surpassing previous methods. This approach demonstrates significant potential in improving the accuracy, efficiency, and clinical applicability of automated NHL subtype classification from histopathological images. © 2025 IAENG International Journal of Computer Science

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

MiT-Unet: Mixed Transformer Unet for Transmission Line Segmentation in UAV Images

引用

IEEE Transactions on Power Delivery 2025年第3期40卷 1279-1288页

作者： Wei, Ning Chen, Jianwei Sun, Shuifa The Hubei Key Laboratory of Intelligent Vision-Based Monitoring for Hydro electric Engineering College of Computer and Information Technology China Three Gorges University Yichang443002 China The Engineering Research Center of Mobile Health Management System Ministry of Education Hangzhou Normal University China

The segmentation of power lines in drone images is one of the challenging tasks in the field of computer vision. Although power lines share the same difficulties with tiny object segmentation, occupying only a very small proportion of pixel areas in the images, the greater challenge is that they also have a very large visual perspective field. Therefore, the results obtained by traditional convolutional neural network-based segmentation methods are still unsatisfactory. To tackle these problems, we propose MiT-Unet (Mixed Transformer Unet), which has an analogous multi-level convolutional neural network structure similar to Unet for encoding and decoding transmission line detailed features. Meanwhile, dealing with excessive scales, we employ an Efficient Self-Attention-based module to enhance the global features of straight lines. Furthermore, in the level transition of this architecture, we propose simple yet efficient upsampling and downsampling modules, TLFM and TLFE, to fuse the global attention feature of power lines. These modules effectively extract and preserve the vulnerable features of power lines during the level transition process. Experimental results demonstrate that our proposed method achieves state-of-the-art performance in transmission line segmentation on the public TTPLA dataset and PLDU dataset. Moreover, the computational efficiency of the proposed model makes it potentially deployable on mobile platforms. The testing code has been released at: https://***/xiachengs/MiT-Unet. ©1986-2012 IEEE.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

7.2.2 On Methodology and system Framework for Knowledge management in Allied system engineering

引用

INCOSE International Symposium 2004年第1期14卷 1437-1449页

作者： Chen, Yuh-Min Chen, Yuh-Jen Kuo, Jen-Yao Wang, Chin-Bin Ho, ChengTer Institute of Manufacturing Engineering National Cheng Kung University Tainan Taiwan System Engineering Center Industrial Technology Research Institute Hsin-Chu Taiwan Dept. of Information Management Nan-Hua University Chia-Yi Taiwan Dept. of Industrial Engineering and Management National Kaohsiung University of Applied Sciences Kaohsiung Taiwan

This paper presents a systematic approach to development of a methodology and a system framework for knowledge management to support allied system engineering. The approach of this research has laid-down four phases: allied system engineering characterization, knowledge identification, analysis and modeling, KM strategy and methodology development, and system development. The methodology consists of a rationale behind the methodology, a life cycle model for knowledge management, and a distributed knowledge management framework. Based on the proposed methodology, a knowledge management system framework is developed using component technology. Besides providing functions for knowledge management and sharing, the system possesses properties to meet the hierarchical, distributed, flexible and dynamic-configurable characteristics of allied system engineering. © 2004 The Authors.

关键词： Knowledge management

来源：评论

学校读者我要写书评

暂无评论

Truthful Mechanism for Resource Allocation and Pricing in Vehicle-Assisted Mobile Edge Computing

引用

IEEE Transactions on Vehicular Technology 2025年第5期74卷 8171-8186页

作者： Liu, Xi Liu, Jun Li, Weidong Qujing Normal University Key Laboratory of Intelligent Sensor and System Design School of Information Engineering Qujing655001 China Qujing Normal University Engineering Research Center of Intelligent System and Advanced Materials Yunnan Province Universities Qujing655001 China Yunnan College of Business Management School of Education Kunming650000 China Yunnan University School of Mathematics and Statistics Kunming650504 China

Mobile edge computing (MEC) provides stable and powerful computing services, and vehicle computing provides rich sensing services. Therefore, we develop vehicle-assisted mobile edge computing (VAMEC), integrating MEC and vehicle computing to maximize their advantages and broaden their applications. We address the resource allocation and pricing problem in VAMEC, in which the vehicle, as a resource provider, collaborates with the MEC servers to provide services to users. To enable MEC servers and vehicles to work in cooperation, we propose a mixed auction model that consists of two-step auctions: the first one-way auction and the second double auction. We consider three types of users based on their characteristics, where users participate in different auctions depending on the types. Users and vehicles are self-interested and may submit untrue values to harm the system's profits. Therefore, we propose the overall truthfulness for the mixed auction model, that is users or vehicles that cannot obtain higher utility by declaring untrue values regardless of which auction they participate in. To the best of our knowledge, this is the first study proposing the overall truthfulness and showing how to design the mechanism that achieves it. We then propose an overall truthfulness mechanism and show it achieves individual rationality, budget balance, and consumer sovereignty. Simulation results indicate that the proposed mechanism can increase social welfare by at least 24%, compared with other mechanisms. © 1967-2012 IEEE.

关键词： Mobile edge computing

来源：评论

学校读者我要写书评

暂无评论

A Non-Sequential Steganography Method Using Perfect Square Quotient Differencing (NSPSQD)

引用

SN Computer Science 2025年第5期6卷 1-26页

作者： Basak, Ratan Kumar Chatterjee, Ritam Dasgupta, Kousik Dutta, Paramartha Computer Science and Engineering Institute of Engineering and Management (IEM) University of Engineering and Management Kolkata Kolkata India Computer Science and Engineering Kalyani Government Engineering College Kalyani India Computer and System Science Visva-Bharati University Bolpur India

In today’s digital world, keeping data safe is a top priority. Two common methods used to protect data are steganography and cryptography. Steganography hides secret data within everyday files (like images, GIFs or videos), while cryptography scrambles the data into an unreadable format. This paper introduces a new way to hide data using a technique called Perfect Square Quotient Differencing. Instead of embedding data in a straight sequence, the method hides information in two steps within the components of an image pixel (called the quotient and remainder). In the first step, a perfect square quantization technique is applied to the quotient part. In the second step, the Two Least Significant Bit (2LSB) method is used on the remainder part. A new range-table is also introduced to help determine how much data can be hidden in the first step. This two-step approach allows a large amount of data to be hidden (about 3 bits per pixel on average). The method was tested on many animated color images, and its performance was measured using tools like Peak-Signal-to-Noise-Ratio (PSNR), Mean Square Error (MSE), Universal Image Quality Index (UIQI), and Payload Curve. The results show that this method works better than several modern steganography techniques. Additionally, tests were conducted to ensure the method is secure against potential attacks. This new algorithm could be particularly useful for protecting digital documents stored in cloud-based platforms, offering a robust and efficient way to keep data safe.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tighter Analysis for Decentralized Stochastic Gradient Method: Impact of Data Homogeneity

引用

IEEE Transactions on Automatic Control 2025年

作者： Li, Qiang Wai, Hoi-To The Chinese University of Hong Kong Dept. of System Engineering & Engineering Management Faculty of Engineering Shatin District Hong Kong Hong Kong

This paper studies the effect of data homogeneity on multi-agent stochastic optimization. We consider the decentralized stochastic gradient (DSGD) algorithm and perform a refined convergence analysis. Our analysis is explicit on the similarity between Hessian matrices of local objective functions which captures the degree of data homogeneity. We illustrate the impact of our analysis through studying the transient time, defined as the minimum number of iterations required for a distributed algorithm to achieve comparable performance as its centralized counterpart. When the local objective functions have similar Hessian, the transient time of DSGD can be as small as for smooth (possibly non-convex) objective functions, for strongly convex objective functions, where is the number of agents and is the spectral gap of graph. These findings provide a theoretical justification for the empirical success of DSGD. Our analysis relies on a novel observation with higher-order Taylor approximation for gradient maps that can be of independent interest. Numerical simulations validate our findings. © 2025 IEEE.

关键词： Optimization algorithms

来源：评论

学校读者我要写书评

暂无评论

A NONPARAMETRIC ROBUST OPTIMIZATION APPROACH FOR CHANCE-CONSTRAINED KNAPSACK PROBLEM

引用

SIAM Journal on Optimization 2025年第2期35卷 739-766页

作者： Xu, Liang Zhang, Chao Xu, Zhou Long, Daniel Zhuoyu School of Business Administration Southwestern University of Finance and Economics Chengdu China Big Data Laboratory on Financial Security and Behavior SWUEF Laboratory of Philosophy and Social Sciences Ministry of Education Chengdu China School of Medical Informatics Chongqing Medical University Chongqing China Department of Logistics Management and Maritime Studies Hong Kong Polytechnic University Hong Kong Department of System Engineering and Engineering Management Chinese University of Hong Kong Hong Kong

A chance-constrained knapsack problem (CCKP) is a knapsack problem restricted by a chance constraint, which ensures that the total capacity constraint under uncertain volume can be violated only up to a given probability threshold. CCKP is challenging to solve due to its combinatorial nature and the involvement of its chance constraint. Existing solution methods for CCKP with tractability guarantees mainly focus on two approaches: (1) a full-information approach (stochastic programming) that assumes the uncertain volume follows certain distributions, such as normal or empirical distribution;(2) a partial-information approach (robust optimization) that adopts specific statistics of the unknown distribution, such as the mean and variance. The existing full-information approach lacks robustness under limited samples due to its strong assumption;the existing partial-information approach can be further improved, as the uncertainty set or distributional ambiguity set can be ameliorated. With these concerns in mind, we propose a nonparametric robust approach for CCKP by involving a novel nonparametric statistic to form a new distributional ambiguity set. Furthermore, we develop an upper bound on the violation probability of the chance constraint under the distributional ambiguity set to approximate CCKP by a deterministic robust counterpart. In terms of solution methodology, we decompose the deterministic robust counterpart into cardinality-constrained knapsack problems, which can be efficiently solved by the proposed dynamic programming algorithm. Computational results show that our proposed solution methods produce better solutions to CCKP compared with existing approaches. © 2025 Society for Industrial and Applied Mathematics.

关键词： Stochastic programming

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：