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Improved Harris Hawks Algorithm and Its Application in Feature Selection

computers, Materials & Continua 2024年第10期81卷 1251-1273页

作者： Qianqian Zhang Yingmei Li Jianjun Zhan Shan Chen School of Computer Science and Information Engineering Harbin Normal UniversityHarbin150025China College of Systems Engineering National University of Defense TechnologyChangsha410073China

This research focuses on improving the Harris’Hawks Optimization algorithm(HHO)by tackling several of its shortcomings,including insufficient population diversity,an imbalance in exploration ***,and a lack of thorough exploitation *** tackle these shortcomings,it proposes enhancements from three distinct perspectives:an initialization technique for populations grounded in opposition-based learning,a strategy for updating escape energy factors to improve the equilibrium between exploitation and exploration,and a comprehensive exploitation approach that utilizes variable neighborhood search along with mutation *** effectiveness of the Improved Harris Hawks Optimization algorithm(IHHO)is assessed by comparing it to five leading algorithms across 23 benchmark test *** findings indicate that the IHHO surpasses several contemporary algorithms its problem-solving ***,this paper introduces a feature selection method leveraging the IHHO algorithm(IHHO-FS)to address challenges such as low efficiency in feature selection and high computational costs(time to find the optimal feature combination and model response time)associated with high-dimensional *** analyses between IHHO-FS and six other advanced feature selection methods are conducted across eight *** results demonstrate that IHHO-FS significantly reduces the computational costs associated with classification models by lowering data dimensionality,while also enhancing the efficiency of feature ***,IHHO-FS shows strong competitiveness relative to numerous algorithms.

关键词： HHO IHHO population diversity energy factor update strategy deep exploitation strategy feature selection

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Effects of altering the ratio of C16:0 and cis-9 C18:1 in rumen bypass fat on growth performance, lipid metabolism, intestinal barrier, cecal microbiota, and inflammation in fattening bulls

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Journal of Animal science and Biotechnology 2024年第5期15卷 2156-2174页

作者： Haixin Bai Haosheng Zhang Congwen Wang Modinat Tolani Lambo Yang Li Yonggen Zhang College of Animal Science and Technology Northeast Agricultural UniversityHarbin 150030China Faculty of Animal Science and Technology Yunnan Agricultural UniversityKunming 650500China

Background C16:0 and cis-9 C18:1 may have different effects on animal growth and health due to unique metabolism in *** study was investigated to explore the different effects of altering the ratio of C16:0 and cis-9 C18:1 in fat supplements on growth performance,lipid metabolism,intestinal barrier,cecal microbiota,and inflammation in fattening *** finishing Angus bulls(626±69 kg,21±0.5 months)were divided into 3 treatments according to the randomized block design:(1)control diet without additional fat(CON),(2)CON+2.5%palmitic acid calcium salt(PA,90%C16:0),and(3)CON+2.5%mixed fatty acid calcium salt(MA,60%C16:0+30%cis-9 C18:1).The experiment lasted for 104 d,after which all the bulls were slaughtered and sampled for *** MA tended to reduce 0–52 d dry matter intake compared to PA(DMI,P=0.052).Compared with CON and MA,PA significantly increased 0–52 d average daily gain(ADG,P=0.027).PA tended to improve the 0–52 d feed conversion rate compared with CON(FCR,P=0.088).Both PA and MA had no significant effect on 52–104 days of DMI,ADG and FCR(P>0.05).PA tended to improve plasma triglycerides compared with MA(P=0.077),significantly increased plasma cholesterol(P=0.002)and tended to improve subcutaneous adipose weight(P=0.066)when compared with CON and *** PA and MA increased visceral adipose weight compared with CON(P=0.021).Only PA increased the colonization of Rikenellaceae,Ruminococcus and Proteobacteria in the cecum,and MA increased Akkermansia abundance(P<0.05).Compared with CON,both PA and MA down-regulated the m RNA expression of Claudin-1 in the jejunum(P<0.001),increased plasma diamine oxidase(DAO,P<0.001)and lipopolysaccharide(LPS,P=0.045).Compared with CON and MA,PA down-regulated the ZO-1 in the jejunum(P<0.001)and increased plasma LPS-binding protein(LBP,P<0.001).Compared with CON,only PA down-regulated the Occludin in the jejunum(P=0.013).Compared with CON,PA and MA significantly up-regulated the expression of TLR-4 and NF-κB

关键词： C16:0 cis-9 C18:1 Finishing bulls Intestinal homeostasis Lipid metabolism Low-grade inflammation

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Thermal Characteristics of Oil Film in Critical Lubrication State of Heavy Hydrostatic Bearing

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Recent Patents on Mechanical Engineering 2024年第4期17卷 304-311页

作者： Yanqin, Zhang Ye, Wu Jiabao, Li Mulan, Wang Zhen, Quan College of Mechanical Engineering Nanjing Institute of Technology Nanjing China College of Mechanical Engineering Harbin University of Science and Technology Harbin China

Background: Lubrication failure has always been a concern in the research of heavy hydrostatic bearings. A preliminary study found that under a certain working condition, the heavy hydrostatic bearing will appear in the condition of zero local flow of oil film, which is called a critical lubrication state. It produces a significant thermal accumulation effect and affects the lubrication performance of the bearing. Objective: This paper takes Q1-205 double rectangular cavity hydrostatic thrust bearing as the research object and adopts the research method combining theoretical analysis, simulation, and experimental test to analyze the temperature rise and characteristics of the bearing when it is in critical lubrication state under different working conditions. Methods: The finite volume method is used to simulate the critical lubrication state under the condition of common load and rotating speed, and the corresponding operating parameters of the critical lubrication of heavy static support are obtained. Results: It is found that when the oil film is in the critical lubrication state, the low temperature zone is concentrated at the bearing position of the oil film, while the high temperature zone is concentrated at the counter-current side sealing edge. Conclusion: The oil film's local temperature rise is intensified, and the heat accumulation phenomenon is serious because the heat cannot be taken away in time. © 2024 Bentham science Publishers.

关键词： Lubrication

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A Quantitative Evaluation of Vector Transcendental Functions on ARMv8-Based Processors

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Journal of computer science & technology 2023年第3期38卷 686-701页

作者：沈洁龙标黄春 College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Transcendental functions are important functions in various high performance computing *** these functions are time-consuming and the vector units on modern processors become wider and more scalable,there is an increasing demand for developing and using vector transcendental functions in such performance-hungry ***,the performance of vector transcendental functions as well as their accuracy remain largely *** address this issue,we perform a comprehensive evaluation of two Single Instruction Multiple Data(SIMD)intrinsics based vector math libraries on two ARMv8 compatible *** first design dedicated microbenchmarks that help us understand the performance behavior of vector transcendental ***,we propose a piecewise,quantitative evaluation method with a set of meaningful metrics to quantify their performance and *** analyzing the experimental results,we find that vector transcendental functions achieve good performance speedups thanks to the vectorization and algorithm ***,vector math libraries can replace scalar math libraries in many cases because of improved performance and satisfactory *** this,the implementations of vector math libraries are still immature,which means further optimization is needed,and our evaluation reveals feasible optimization solutions for future vector math libraries.

关键词： transcendental function vector math library piecewise quantitative evaluation microbenchmarking ARMv8-based processor

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Classifier Retraining with Gaussian-distributed Prototypes for Class-Imbalanced Federated Medical Image Classification

Classifier Retraining with Gaussian-distributed Prototypes f...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Pan, Haiwei Chen, Chunling Zhang, Kejia Li, Zhe Yu, Fengming Harbin Engineering University College of Computer Science and Technology Harbin China

ISBN: (纸本)9798350386226

Federated learning enables collaborative learning across distributed medical institutions without centralizing data. However, existing studies often overlook class imbalance in medical images, which can degrade model performance, especially for minority classes. In this paper, we propose FedCRGP, a method that uses Gaussian-distributed prototypes to address class imbalance in federated medical image classification. These prototypes incorporate class variance to enhance representation learning. Class-aware Gaussian Prototype Learning (CGPL) is introduced to improve intra-class similarity and reduce interclass similarity by aligning class features around the Gaussian-distributed prototypes. Local and global features sampled from these prototypes are fused to retrain the classifier, mitigating bias caused by class imbalance. Experiments on two medical image classification datasets demonstrate its superior performance, particularly in multi-class scenarios. © 2024 IEEE.

关键词： Federated learning

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Text Clustering and Natural Language Processing Based Dialogue System Model for Relieving Learning Weariness 24

Text Clustering and Natural Language Processing Based Dialog...

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3rd International Conference on computer, Artificial Intelligence and Control Engineering, CAICE 2024

作者： Yu, Bo Lu, Mingde Shi, Yi Lin, Juxing Zeng, Mingjie School of Computer Science and Technology Harbin University of Science and Technology Harbin China

ISBN: (纸本)9798400716942

Learning weariness is a common psychological problem, which will affect students' learning effect and life quality. Currently, most ways to relieve the learning weariness require the intervention of a professional counselor or teacher, but these resources are often limited or difficult to access. In order to provide a low cost, high efficiency and easy to use tool for relieving the learning weariness, this paper introduces a dialogue system model based on text clustering algorithm and natural language processing algorithm to relieve the learning weariness of students. This dialogue system model provides learning emotion assessment function, learning weariness relieving function, and self-counseling advice function for students. Among them, the learning weariness relieving function is the highlight of this system model. Text clustering algorithm is the core technology of this function, which is able to classify the corpus according to different topics and train a specialized dialogue mod-el for each topic using natural language processing algorithm. In this way, when students ask questions, the learning weariness relieving function can select the most appropriate dialogue model to generate replies according to the topic of the question, so as to improve the quality and effect of the dialogue. In this paper, BLEU value is used as the evaluation index of the dialogue model, and F1-score is used as the evaluation index of text clustering model. Experimental results show that the dialogue system model can accurately distinguish the topic of the question and generate high quality replies. Therefore, this paper plans to improve the quality of the corpus used to train the models and try other data augmentation techniques in the future. © 2024 ACM.

关键词： Students

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A Novel CAPTCHA Recognition System Based on Refined Visual Attention

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computers, Materials & Continua 2025年第4期83卷 115-136页

作者： Zaid Derea Beiji Zou Xiaoyan Kui Monir Abdullah Alaa Thobhani Amr Abdussalam School of Computer Science and Engineering Central South UniversityChangsha410083China College of Computer Science and Information Technology Wasit UniversityWasit52001Iraq Department of Computer Science and Artificial Intelligence College of Computing and Information TechnologyUniversity of BishaBisha67714Saudi Arabia Electronic Engineering and Information Science Department University of Science and Technology of ChinaHefei230026China

Improving website security to prevent malicious online activities is crucial,and CAPTCHA(Completely Automated Public Turing test to tell computers and Humans Apart)has emerged as a key strategy for distinguishing human users from automated ***-based CAPTCHAs,designed to be easily decipherable by humans yet challenging for machines,are a common form of this ***,advancements in deep learning have facilitated the creation of models adept at recognizing these text-based CAPTCHAs with surprising *** our comprehensive investigation into CAPTCHA recognition,we have tailored the renowned UpDown image captioning model specifically for this *** approach innovatively combines an encoder to extract both global and local features,significantly boosting the model’s capability to identify complex details within CAPTCHA *** the decoding phase,we have adopted a refined attention mechanism,integrating enhanced visual attention with dual layers of Long Short-Term Memory(LSTM)networks to elevate CAPTCHA recognition *** rigorous testing across four varied datasets,including those from Weibo,BoC,Gregwar,and Captcha 0.3,demonstrates the versatility and effectiveness of our *** results not only highlight the efficiency of our approach but also offer profound insights into its applicability across different CAPTCHA types,contributing to a deeper understanding of CAPTCHA recognition technology.

关键词： Text-based CAPTCHA recognition refined visual attention web security computer vision

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CALTM:A Context-Aware Long-Term Time-Series Forecasting Model

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computer Modeling in Engineering & sciences 2024年第4期139卷 873-891页

作者： Canghong Jin Jiapeng Chen Shuyu Wu Hao Wu Shuoping Wang Jing Ying School of Computer and Computing Science Hangzhou City UniversityHangzhou310015China School of Computer Science and Engineering Macao University of Science and TechnologyMacao999078China College of Computer Science and Technology Zhejiang UniversityHangzhou310058China

Time series data plays a crucial role in intelligent transportation *** flow forecasting represents a precise estimation of future traffic flow within a specific region and time *** approaches,including sequence periodic,regression,and deep learning models,have shown promising results in short-term series ***,forecasting scenarios specifically focused on holiday traffic flow present unique challenges,such as distinct traffic patterns during vacations and the increased demand for long-term ***,the effectiveness of existing methods diminishes in such ***,we propose a novel longterm forecasting model based on scene matching and embedding fusion representation to forecast long-term holiday traffic *** model comprises three components:the similar scene matching module,responsible for extracting Similar Scene Features;the long-short term representation fusion module,which integrates scenario embeddings;and a simple fully connected layer at the head for making the final *** results on real datasets demonstrate that our model outperforms other methods,particularly in medium and long-term forecasting scenarios.

关键词： Traffic volume forecasting scene matching multi module fusion

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Modeling Price-Aware Session-Based Recommendation Based on Graph Neural Network

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computers, Materials & Continua 2023年第7期76卷 397-413页

作者： Jian Feng Yuwen Wang Shaojian Chen College of Computer Science&Technology Xi’an University of Science and TechnologyXi’an710600China

Session-based Recommendation(SBR)aims to accurately recom-mend a list of items to users based on anonymous historical session *** methods for SBR suffer from several limitations:SBR based on Graph Neural Network often has information loss when constructing session graphs;Inadequate consideration is given to influencing factors,such as item price,and users’dynamic interest evolution is not taken into account.A new session recommendation model called Price-aware Session-based Recommendation(PASBR)is proposed to address these *** constructs session graphs by information lossless approaches to fully encode the original session information,then introduces item price as a new factor and models users’price tolerance for various items to influence users’*** addition,PASBR proposes a new method to encode user intent at the item category level and tries to capture the dynamic interest of users over ***,PASBR fuses the multi-perspective features to generate the global representation of users and make a ***,the intent,the short-term and long-term interests,and the dynamic interests of a user are *** on two real-world datasets show that PASBR can outperform representative baselines for SBR.

关键词： Session-based recommendation graph neural network price-aware intention dynamic interest

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Image Enhancement via Associated Perturbation Removal and Texture Reconstruction Learning

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IEEE/CAA Journal of Automatica Sinica 2024年第11期11卷 2253-2269页

作者： Kui Jiang Ruoxi Wang Yi Xiao Junjun Jiang Xin Xu Tao Lu IEEE the School of Computer Science and Technology Harbin Institute of Technology Zhengzhou Research Institute Harbin Institute of Technology the School of Artificial Intelligence Jianghan University the School of Geodesy and Geomatics Wuhan University the Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology the School of Computer Science and Engineering and also with the Hubei Province Key Laboratory of Intelligent Robot Wuhan Institute of Technology

Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distortion. However, current technologies have barely explored the correlation between perturbation removal and background restoration, consequently struggling to generate high-naturalness content in challenging scenarios. In this paper, we rethink the image enhancement task from the perspective of joint optimization: Perturbation removal and texture reconstruction. To this end, we advise an efficient yet effective image enhancement model, termed the perturbation-guided texture reconstruction network(PerTeRNet). It contains two subnetworks designed for the perturbation elimination and texture reconstruction tasks, respectively. To facilitate texture recovery,we develop a novel perturbation-guided texture enhancement module(PerTEM) to connect these two tasks, where informative background features are extracted from the input with the guidance of predicted perturbation priors. To alleviate the learning burden and computational cost, we suggest performing perturbation removal in a sub-space and exploiting super-resolution to infer high-frequency background details. Our PerTeRNet has demonstrated significant superiority over typical methods in both quantitative and qualitative measures, as evidenced by extensive experimental results on popular image enhancement and joint detection tasks. The source code is available at https://***/kuijiang94/PerTeRNet.

关键词： Association learning attention mechanism image enhancement perturbation modeling

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