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2024 China Automation Congress, CAC 2024

作者： Jun, Yang Yan, Xiong Chunjie, Zhou School of Computer Science and Engineering Changsha University Changsha China School of Traffic & Transportation Engineering Central South University Changsha China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350368604

With the extensive application of technologies like Ethernet and integrated control in high-speed trains, onboard networks encounter mounting security challenges, making the assurance of their secure and stable operation a pressing issue. Since train onboard control and monitoring systems require high reliability and continuous stability, implementing security strategies can compromise system functionality, resources, and costs. Therefore, this paper presents a risk-driven method for decision-making on security strategies, examining how to select suitable security measures that minimize security risks while maximizing security benefits. A risk assessment approach is proposed, which accounts for the propagation of attack impacts based on system topology and functional features. Finally, a network simulation system is established, referencing the topology and functional specifications of the CR300AF Fuxing EMU, and experimental outcomes confirm a close alignment between the analysis results and actual train operations. © 2024 IEEE.

关键词： Risk assessment

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Enhancing Effective Spectrum Utilization in 6G Cellular Networks via Sharing Algorithms 5th

Enhancing Effective Spectrum Utilization in 6G Cellular Netw...

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5th International Conference on Data science, Machine Learning and Applications, ICDSMLA 2023

作者： kudari, Jayashree M. Garg, Aanchal Sridevi, S. Savita Department of Computer Science and Information Technology Jain University Karnataka Bangalore India Department of Electronic & Communication Engineering School of Engineering and Computing Dev Bhoomi Uttarakhand University Manduwala Dehradun Navgaon India School of Computer Science and Engineering Presidency University Karnataka Bengaluru India Maharishi School of Engineering & Technology Maharishi University of Information Technology Uttar Pradesh Lucknow India

ISBN: (纸本)9789819780426

The emerging 6G mobile network technology presents an opportunity to noticeably increase spectrum utilization in comparison to previous generations. This paper introduces a singular sharing algorithm to correctly utilize the spectrum in 6G mobile networks. This set of rules leverages device mastering techniques to dynamically calculate a charge primarily based at the average channel usage and bandwidth usage through distinct users. Moreover, it gives a dispensed mechanism to define the resource allocation method used in different communique situations. The proposed set of rules is powerful, reliable, and cozy, and it is able to efficaciously apply spectrum sharing amongst unique users to maximize spectral performance. Simulation results display that the proposed set of rules achieves giant improvements in spectral efficiency as compared to both a traditional unmarried-mobile method, and a present sharing algorithm proposed in the literature. Finally, experimental results are supplied, which demonstrate the effectiveness of the proposed set of rules in real-world check setups. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wireless networks

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Dynamic Multi-Layer Perceptron for Fetal Health Classification Using Cardiotocography Data

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computers, Materials & Continua 2024年第8期80卷 2301-2330页

作者： Uddagiri Sirisha Parvathaneni Naga Srinivasu Panguluri Padmavathi Seongki Kim Aruna Pavate Jana Shafi Muhammad Fazal Ijaz Department of Computer Science and Engineering Prasad V Potluri Siddhartha Institute of TechnologyVijayawada520007India Amrita School of Computing Amrita Vishwa VidyapeethamAmaravatiAndhra Pradesh522503India Department of Tele informatics Engineering Federal University of CearáFortaleza60455-970Brazil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramGunturAndhra Pradesh522302India Department of Computer Engineering Chosun UniversityGwangju61452Republic of Korea School of CSIT Symbiosis Skills and Professional UniversityPune412101India Department of Computer Engineering and Information College of Engineering inWadi AlddawasirPrince Sattam bin Abdulaziz UniversityWadi Alddawasir11991Saudi Arabia School of IT and Engineering Melbourne Institute of TechnologyMelbourne3000Australia

Fetal health care is vital in ensuring the health of pregnant women and the *** check-ups need to be taken by the mother to determine the status of the fetus’growth and identify any potential *** know the status of the fetus,doctors monitor blood reports,Ultrasounds,cardiotocography(CTG)data,***,in this research,we have considered CTG data,which provides information on heart rate and uterine contractions during *** researchers have proposed various methods for classifying the status of fetus *** processing of CTG data is time-consuming and ***,automated tools should be used to classify fetal *** study proposes a novel neural network-based architecture,the Dynamic Multi-Layer Perceptron model,evaluated from a single layer to several layers to classify fetal *** strategies were applied,including pre-processing data using techniques like Balancing,Scaling,Normalization hyperparameter tuning,batch normalization,early stopping,etc.,to enhance the model’s performance.A comparative analysis of the proposed method is done against the traditional machine learning models to showcase its accuracy(97%).An ablation study without any pre-processing techniques is also *** study easily provides valuable interpretations for healthcare professionals in the decision-making process.

关键词： Fetal health cardiotocography data deep learning dynamic multi-layer perceptron feature engineering

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On the Smoothed Complexity of Combinatorial Local Search 51

On the Smoothed Complexity of Combinatorial Local Search

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51st International Colloquium on Automata, Languages, and Programming, ICALP 2024

作者： Giannakopoulos, Yiannis Grosz, Alexander Melissourgos, Themistoklis School of Computing Science University of Glasgow United Kingdom School of Computation Information and Technology Technical University of Munich Germany School of Computer Science and Electronic Engineering University of Essex United Kingdom

ISBN: (纸本)9783959773225

We propose a unifying framework for smoothed analysis of combinatorial local optimization problems, and show how a diverse selection of problems within the complexity class PLS can be cast within this model. This abstraction allows us to identify key structural properties, and corresponding parameters, that determine the smoothed running time of local search dynamics. We formalize this via a black-box tool that provides concrete bounds on the expected maximum number of steps needed until local search reaches an exact local optimum. This bound is particularly strong, in the sense that it holds for any starting feasible solution, any choice of pivoting rule, and does not rely on the choice of specific noise distributions that are applied on the input, but it is parameterized by just a global upper bound on the probability density. The power of this tool can be demonstrated by instantiating it for various PLS-hard problems of interest to derive efficient smoothed running times (as a function of and the input size). Most notably, we focus on the important local optimization problem of finding pure Nash equilibria in Congestion Games, that has not been studied before from a smoothed analysis perspective. Specifically, we propose novel smoothed analysis models for general and Network Congestion Games, under various representations, including explicit, step-function, and polynomial resource latencies. We study PLS-hard instances of these problems and show that their standard local search algorithms run in polynomial smoothed time. Further applications of our framework to a wide range of additional combinatorial problems can be found in the full version of our paper. © Yiannis Giannakopoulos, Alexander Grosz, and Themistoklis Melissourgos.

关键词： Probability distributions

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Analysis of breast cancer prediction and visualisation using machine learning models

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International Journal of Cloud Computing 2022年第1期11卷 43-60页

作者： Magesh, G. Swarnalatha, P. School of Information Technology and Engineering VIT University Vellore India School of Computer Science and Engineering VIT University Vellore India

Breast cancer is one of the most commonly occurring malignancies cancer in women, and there are millions of new cases diagnosed among women's and over 400,000 deaths annually worldwide. In our dataset, we have 30 real-valued attributes as features which are computed from the fine needle aspirate (FNA) test. Our dataset values are calculated from the processed image of a first needle aspirate test of a breast mass. Our input values are extracted from the digitalised image of the FNA test. There are many algorithms used for prediction systems. We are choosing the best algorithms based on the precision result, accuracy, and error rate. We are making a comparison of an effective way of applying algorithms and classifying data. We have different machine learning algorithms, a performance comparison conducted between those algorithms on the breast cancer datasets. Data visualisation and descriptive statistics have been presented. SVM with all features achieves 95% of precision, recall, and F1-score. After tuning the SVM parameters, accuracy has improved to 97%. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Forecasting

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Using Nature-Inspired Optimization Algorithms and Machine Learning to Optimize Hadoop Resource Scheduling

Using Nature-Inspired Optimization Algorithms and Machine Le...

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2024 IEEE International Conference on Intelligent Systems and Advanced Applications, ICISAA 2024

作者： Muppidi, Satish Maram, Balajee Satish, Aravapalli Rama Manivannan, B. GMR Institute of Technology Departnent of Computer Science and Engineering Rajam India SR University School of Computer Science and Artificial Intelligence Telangana Warangal506371 India VIT-AP University School of Computer Science & Engineering Andhra Pradesh India Vivekanandha College of Engineering for Women Department of CSE Tiruchengode India

ISBN: (纸本)9798331539948

This paper investigates the ability of utilizing nature-inspired optimization techniques alongside machine learning (ML) to enhance resource adjustment in Hadoop clusters. The use of ML models with adaptive optimization methodology is aimed at minimizing the time incurred to complete a task in addition to enhancing the efficiency of resource utilization. It reviews the existing Hadoop scheduling approaches and focusing on machine learning and bio-inspired techniques. For the categorization of workloads and prediction of resource needs for a specific future time, the suggested approach includes using ML algorithms like supervised/unsupervised or reinforcement ***, new efficient work schedules and resources distribution will be used due to the nature-inspired optimization algorithms, for example, the GA, PSO. This research framework for scheduling in Hadoop will be created that will incorporate elements of artificial intelligence by using machine learning to provide expectations along with bio-inspired techniques. The tests will indicate how much resources will be utilised, how long certain jobs take, how well and scalable or the system is using actual or simulated data sets. Comprehensive comparative assessment with the traditional and improved approaches will reveal the efficiency of the proposed methodology. The results part consist of optimised approach for resource distribution, efficient flexibility in handling the workloads, and increased Hadoop specialised cluster reinforcement for scalability and heterogeneously challenging data processing activities. © 2024 IEEE.

关键词： Genetic algorithms

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Identification of Brain Diseases using Image Classification: A Deep Learning Approach 2

Identification of Brain Diseases using Image Classification:...

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

作者： Singh, Jagendra Singh, Akansha Singh, Krishna Kant Lal, Bechoo William, Rithwik Arthur Turukmane, Anil V. Kumar, Advait School of Computer Science Engineering and Technology Bennett University Greater Noida201310 India Delhi Technical Campus Greater Noida201310 India Department of Computer Science and Engineering Konenru Lakshmaiah Education Foundation vaddeswaram India School of Computer Science and Engineering VIT - AP University Vijaywada Amaravati India

Brain diseases are a growing concern in healthcare, with an estimated 50 million people worldwide living with dementia and 15 million new cases each year. This research paper explores the significance of early identification and diagnosis in mitigating the impact of brain diseases on individuals and society at large. Moreover, the study delves into the current state of diagnostic practices, highlighting the limitations and emerging opportunities in the field. The paper concludes by advocating for increased research, improved access to advanced medical technologies, and enhanced training for healthcare professionals to address the growing burden of brain diseases effectively. © 2024 Elsevier B.V.. All rights reserved.

关键词： Image classification

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Double-layer Waveguide System for Improving the Optical Efficiency

Double-layer Waveguide System for Improving the Optical Effi...

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International Conference on Display technology, 2024

作者： Guo, Yusong Cai, Jiahao Zhang, Zhensong Guo, Min Feng, Qibin Wang, Zi Lv, Guoqiang School of Instrument Science and Opto-Electronics Engineering Hefei University of Technology Anhui Hefei China Seeya Technology Corp Anhui Hefei China Special Display and Imaging Technology Innovation Center of Anhui Province National Engineering Laboratory of Special Display Technology Academy of Photoelectric Technology Hefei University of Technology Anhui Hefei China

Conventional volume holographic waveguide display devices have the disadvantage of low optical efficiency, making it difficult to meet the needs of outdoor applications. Back-coupling loss (BCL) can severely decrease the optical efficiency of VHG-based waveguide systems and thin substrate and angular selectivity of the volume holographic grating (VHG) are the two main reasons of BCL. In this paper, a simple and effective double-layer waveguide system is proposed to degrade BCL. The simulation results show that the optical efficiency of the double-layer waveguide system is improved from 5.57% of the single-layer waveguide to 7.41% of the double-layer waveguide. © 2024 John Wiley and Sons Inc. All rights reserved.

关键词： Efficiency

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On Differentiation Among Pilot Signals of Multiple Mobile Targets in Retro-Reflective Beamforming for Wireless Power Transmission

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engineering 2023年第11期30卷 55-62页

作者： Xin Wang Long Li Tie Jun Cui Mingyu Lu School of Electrical Engineering Chongqing UniversityChongqing 400044China School of Electronic Engineering Xidian UniversityXi’an 710071China State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast UniversityNanjing 210096China Department of Electrical and Computer Engineering West Virginia University Institute of TechnologyBeckleyWV 25801USA

An experimental study is conducted on several retro-reflective beamforming schemes for wireless power transmission to multiple wireless power receivers(referred to herein as“targets”).The experimental results demonstrate that,when multiple targets broadcast continuous-wave pilot signals at respective frequencies,a retro-reflective wireless power transmitter is capable of generating multiple wireless power beams aiming at the respective targets as long as the multiple pilot signals are explicitly separated from one another by the wireless power ***,various practical complications are identified when the pilot signals of multiple targets are not appropriately differentiated from each other by the wireless power ***,when multiple pilot signals are considered to be carried by the same frequency,the wireless power transmission performance becomes heavily dependent on the interaction among the pilot signals,which is highly undesirable in *** conclusion,it is essential for a retro-reflective wireless power transmitter to explicitly discriminate multiple targets’pilot signals among each other.

关键词： Wireless power transmission Microwave antenna array Retro-reflective beamforming Pilot signal Multiple access

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Label-Enhanced Cross-Modal Hashing with Dual-Semantic Learning 25th

Label-Enhanced Cross-Modal Hashing with Dual-Semantic Learn...

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25th International Conference on Web Information Systems engineering, WISE 2024

作者： Fang, Ziye Teng, Luyao Zheng, Zefeng Zhang, Wei Teng, Shaohua School of Computer Science and Technology Guangdong University of Technology Guangzhou510006 China School of Information Engineering Guangzhou Panyu Polytechnic Guangzhou511483 China

ISBN: (纸本)9789819605668

Due to its excellent storage and retrieval performance, Cross-Modal Hashing (CMH) has garnered widespread attention in recent years. However, current methods still face two major limitations: 1) most methods fail to adequately address noise in the labels, 2) many methods neglect learning the correlations between labels. To address these issues, we propose Label-enhanced Cross-modal Hashing with Dual-semantic Learning (LCHDL) in this study. LCHDL mainly consists of two parts, i.e., DeNoise Label Semantics Learning (DNLSL) and Static Label Correlations Embedding (SLCE). DNLSL uses low-rank and sparse representation to reduce noise containing in the labels. SLCE employs a relaxation strategy to achieve static label correlations embedding. Experiments on two benchmark datasets demonstrate that the performance of LCHDL surpasses many state-of-the-art methods. The source code for LCHDL is publicly available at https://***/Fizzyf/LCHDL. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Contrastive Learning

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