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32nd IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2025

作者： Yang, Xixuan Jia, Tong Li, Ying Huang, Gang School of Software and Microelectronics Peking University Beijing China Institute for Artificial Intelligence Peking University Beijing China National Key Laboratory of Data Space Technology and System Beijing China Peking University National Engineering Research Center for Software Engineering Beijing China

ISBN: (纸本)9798331535100

The development of effective diagnostic methodolo-gies for software system failures is of paramount importance. Traditional methods, which rely on specialized terminology and intricate reasoning, require users to have a technical background, resulting in reduced flexibility and decreased user-friendliness. With the rise of generative large language models, optimizing human-computer interaction has become a critical area of focus. Additionally, the inherent intelligence and extensive knowledge of large language models make them both easy and effective to employ for fault diagnosis assistance. We introduce IFKG, an advanced tool for diagnosing software system failures. IFKG integrates generative large language models with knowledge graphs, employing natural language interactions to implement fault detection and deliver solutions. IFKG enables users to upload descriptive problems, retrieve pertinent information from the knowledge graph, and present diagnostic results in natural language. Our accuracy assessments across diverse software system failures indicate that the IFKG provides targeted and actionable recommendations, effectively assisting users in ad-dressing a range of software system issues. The tool is available on GitHub at https://***/mako-xxlIFKG, and the demo video can be found on YouTube: https://***2vgZm2hk. © 2025 IEEE.

关键词： knowledge graph LLM software fault diagnosis

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The OsWRKY72-OsAAT30/OsGSTU26 module mediates reactive oxygen species scavenging to drive heterosis for salt tolerance in hybrid rice

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Journal of Integrative Plant Biology 2024年第4期66卷 709-730页

作者： Citao Liu Bigang Mao Yanxia Zhang Lei tian Biao Ma Zhuo Chen Zhongwei Wei Aifu Li Ye Shao Gongye Cheng Lingling Li Wenyu Li Di Zhang Xiaoping Ding Jiangxiang Peng Yulin Peng Jiwai He Nenghui Ye Dingyang Yuan Chengcai Chu Meijuan Duan Hunan Provincial Key Laboratory of Stress Biology College of AgricultureHunan Agricultural UniversityChangsha 410128China State Key Laboratory of Hybrid Rice Hunan Hybrid Rice Research CenterChangsha 410125China College of Agriculture South China Agricultural UniversityGuangzhou 510642China State Key Laboratory of Wheat and Maize Crop Science Center for Crop Genome EngineeringCollege of AgronomyHenan Agricultural UniversityZhengzhou 450002China College of Horticulture Fujian Agriculture and Forestry UniversityFuzhou 350002China Department of Computational Medicine and Bioinformatics University of MichiganAnn ArborMI 48109 USA Biobin Data Science Co. Ltd.Changsha 410221China

Hybrid rice(Oryza sativa)generally outperforms its inbred parents in yield and stress tolerance,a phenomenon termed heterosis,but the underlying mechanism is not completely ***,we combined transcriptome,proteome,physiological,and heterosis analyses to examine the salt response of super hybrid rice Chaoyou1000(CY1000).In addition to surpassing the mean values for its two parents(mid-parent heterosis),CY1000 exhibited a higher reactive oxygen species scavenging ability than both its parents(over-parent heterosis or heterobeltiosis).Nonadditive expression and allele-specific gene expression assays showed that the glutathione S-transferase gene OsGSTU26 and the amino acid transporter gene OsAAT30 may have major roles in heterosis for salt tolerance,acting in an overdominant fashion in ***,we identified OsWRKY72 as a common transcription factor that binds and regulates OsGSTU26 and *** salt-sensitive phenotypes were associated with the OsWRKY72^(paternal)genotype or the OsAAT30^(maternal)genotype in core rice germplasm ***72^(paternal)specifically repressed the expression of OsGSTU26 under salt stress,leading to salinity sensitivity,while OsWRKY72^(maternal)specifically repressed OsAAT30,resulting in salinity *** results suggest that the OsWRKY72-OsAAT30/OsGSTU26 module may play an important role in heterosis for salt tolerance in an overdominant fashion in CY1000 hybrid rice,providing valuable clues to elucidate the mechanism of heterosis for salinity tolerance in hybrid rice.

关键词： allele-specific gene expression(ASE) heterosis hybrid rice nonadditive effect(NAE) salt tolerance transcriptome and proteome

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News Recommendation with Multi-views Emotion Analysis 22

News Recommendation with Multi-views Emotion Analysis

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Proceedings of the 4th International Conference on Advanced Information Science and System

作者： Han Yun Xin Deng Yulu Du Key Laboratory of Data Engineering and Visual Computing Chongqing University of Posts and Telecommunications China

ISBN: (纸本)9781450397933

News recommendation aiming to find attractive news for users has been received many attentions in recent years. Existing news recommendation methods mainly focus on modeling user preference based on the interaction behaviors between users and news without the consideration of emotion information in the interaction. However, emotion information also plays an important role in improving the accuracy of news recommendation. In this paper, we propose an emotion analysis method for news recommendation with using multi-views to explore the impact of emotion information during the process of user's decision making. The emotion features extracted by the method are combined with the content features of the news to provide a comprehensive feature representation of the candidate news to improve the performance of recommendation. Experiments on real-world datasets show the effectiveness of the proposed method in improving accuracy of news recommendation.

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An Empirical Study on the Tourism Image of Nanjing from the Perspective of International Students 7th

An Empirical Study on the Tourism Image of Nanjing from the ...

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7th International Conference on Artificial Intelligence and Security, ICAIS 2021

作者： Han, Pu Zhang, Mingtao Yao, Mingxiu Hui, Zhenrong Chen, Meitong School of Management Nanjing University of Posts and Telecommunications Nanjing210023 China Jiangsu Provincial Key Laboratory of Data Engineering and Knowledge Service Nanjing210023 China

ISBN: (纸本)9783030786175

International students are a special group in Chinese cities, and their tourism image perception has important research significance for urban tourism construction. Based on the destination tourism image model proposed by Baloglu and McCleary, the tourism image of Nanjing is divided into three aspects: cognitive image, emotional image and overall image. Aiming at the international student group in Nanjing, the questionnaire survey was used to obtain the perception data of the group’s tourism image in Nanjing with SPSS. The empirical research on the tourism image of Nanjing was carried out from three aspects: tourism image perception factor, overall image perception and representative attractions. The study found that in the structured part of the dimension, international students are most satisfied with "urban environment" and least concerned about "attractions". Through the single factor measurement, the most satisfied one is the rich historical and cultural heritage, and the most dissatisfied one is the crowded urban environment. In the unstructured part of the international students on Nanjing tourism image, the overall satisfaction is high, in which the destination image perception of the "delicious food" is the best. In the perception of urban tourism image, the perception of "a beautiful city" is the best. The analysis of the characteristics of social population structure shows obvious individualized difference. Boys tend to Zhongshan mausoleum, and girls are more inclined to Confucius Temple Qinhuai scenery belt. © 2021, Springer Nature Switzerland AG.

关键词： Surveys

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Steel Defect Detection Algorithm Based on Multiobjective ENAS Sharing Strategy 24

Steel Defect Detection Algorithm Based on Multiobjective ENA...

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2nd International Conference on Frontiers of Intelligent Manufacturing and Automation, CFIMA 2024

作者： Zhao, Tianchen Dong, Zhiming Wang, Xianpeng National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University Shenyang China Ministry of Education Shenyang China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Northeastern University Shenyang China

ISBN: (纸本)9798400710681

When employing the network architecture search approach for designing a steel surface defect detector, there are issues with conflicting evaluation metrics and limited computational resources. To address this challenge, we propose a multiobjective evolutionary sharing strategy-based network architecture search method (MESNAS). MESNAS defines network architecture search as a bi-level multiobjective optimization problem combined with a weight sharing acceleration strategy designed to quickly and simultaneously optimize the accuracy and complexity of classification models. A refined search space suitable for different image classification and detection tasks is designed. Using the MOEA/D algorithm, which incorporates a variable-length encoding scheme, the search space is co-utilized and explored through targeted improvements to the crossover and mutation operators in the offspring generation process. The optimal network architecture obtained from the search is tested on the concrete surface defect classification task, and the steel continuous casting slab surface defect detection task. The experimental results show that the proposed algorithm has good model performance and portability in image classification as well as defect detection tasks with different data complexities and different categories. © 2024 Copyright held by the owner/author(s).

关键词： Continuous casting

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Immunometabolism:a new dimension in immunotherapy resistance

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Frontiers of Medicine 2023年第4期17卷 585-616页

作者： Chaoyue Xiao Wei Xiong Yiting Xu Ji’an Zou Yue Zeng Junqi Liu Yurong Peng Chunhong Hu Fang Wu Department of Oncology The Second Xiangya HospitalCentral South UniversityChangsha 410011China NHC Key Laboratory of Carcinogenesis and Key Laboratory of Carcinogenesis and Cancer Invasion of the Chinese Ministry of Education Cancer Research InstituteCentral South UniversityChangsha 410078China Xiangya School of Medicine Central South UniversityChangsha 410013China Hunan Cancer Mega-Data Intelligent Application and Engineering Research Centre Changsha 410011China Hunan Key Laboratory of Early Diagnosis and Precision Therapy in Lung Cancer The Second Xiangya HospitalCentral South UniversityChangsha 410011China Hunan Key Laboratory of Tumor Models and Individualized Medicine The Second Xiangya HospitalCentral South UniversityChangsha 410011China

Immune checkpoint inhibitors(ICIs)have demonstrated unparalleled clinical responses and revolutionized the paradigm of tumor treatment,while substantial patients remain unresponsive or develop resistance to ICIs as a single agent,which is traceable to cellular metabolic *** dysregulated metabolism has long been adjudged as a hallmark of tumor,it is now increasingly accepted that metabolic reprogramming is not exclusive to tumor cells but is also characteristic of ***,people used to pay more attention to the effect of tumor cell metabolism on immunocytes,but in practice immunocytes interact intimately with their own metabolic function in a way that has never been realized before during their activation and differentiation,which opens up a whole new frontier called *** metabolic intervention for tumor-infiltrating immunocytes could offer fresh opportunities to break the resistance and ameliorate existing ICI immunotherapy,whose crux might be to ascertain synergistic combinations of metabolic intervention with ICIs to reap synergic benefits and facilitate an adjusted anti-tumor immune ***,we elaborate potential mechanisms underlying immunotherapy resistance from a novel dimension of metabolic reprogramming in diverse tumor-infiltrating immunocytes,and related metabolic intervention in the hope of offering a reference for targeting metabolic vulnerabilities to circumvent immunotherapeutic resistance.

关键词： immune cell immunometabolism metabolic reprogramming immunotherapy resistance tumor microenvironment immune checkpoint inhibitor

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A Robust key Exchange and Tamper-Resistant Protocol for HAN and NAN Networks in Smart Grids

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IEEE Internet of Things Journal 2025年第12期12卷 21394-21403页

作者： Faizan Ayub, Muhammad Li, Xiong Mahmood, Khalid Shamshad, Salman Kumar Das, Ashok Wang, Guijuan University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu611731 China National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Hyderabad Center for Security Theory and Algorithmic Research Hyderabad500032 India Korea University College of Informatics Department of Computer Science and Engineering Seoul02841 Korea Republic of Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan250353 China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan250353 China

Smart grids (SGs) rely on home area networks (HANs) and neighborhood area networks (NANs) to ensure efficient power distribution, real-time monitoring, and seamless communication between smart devices. Despite these advantages, the use of public communication channels in HAN and NAN networks introduces critical challenges, such as vulnerability to impersonation, physical tampering, and scalability issues in resource-constrained environments. These issues compromise the stability, reliability, and security of SG environments. Existing protocols often fail to adequately address these challenges, particularly in ensuring resistance to physical tampering of supply lines and impersonation attacks. Additionally, they struggle to minimize the computation, communication, and energy costs associated with securing a resource-constrained SG environment. Therefore, we propose a robust key exchange and tamper-resistant protocol for HAN and NAN networks to address these limitations. The proposed protocol leverages the physical unclonable function (PUF) mechanism to offer physical tampering resistance to smart meters. We validate our protocol formally using the Random or Real (RoR) model, which confirms its security robustness. Additionally, our informal security analysis highlights the protocol’s resilience against impersonation, physical tampering attacks, etc. We analyze and compare the performance of the proposed protocol, which further demonstrates our protocol’s effectiveness and security compared to competing protocols. Moreover, the proposed protocol achieves resource efficiency with 45.99% and 58.85% substantial reductions in computation overhead and energy overhead, respectively, compared to competing protocols. These results showcase the protocol’s enhanced security and practicality for resource-constrained SG environments. © 2014 IEEE.

关键词： Authentication Protocol

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Lightweight Remote Sensing Target Detection Algorithm Based on Improved YOLOv5 16th

Lightweight Remote Sensing Target Detection Algorithm Based ...

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16th International Conference on Genetic and Evolutionary Computing, ICGEC 2024

作者： Wang, Chaomin Dong, Fang Liang, Sheng Yu, Wanxin Wu, Kaixian Yu, Long Wenfeng, Wang School of Information Engineering Nanchang Institute of Technology Nanchang330099 China Jiangxi Province Key Laboratory of Smart Water Conservancy Nanchang Institute of Technology Nanchang330099 China School of Statistics and Data Science Jiangxi University of Finance and Economics Nanchang330013 China

ISBN: (纸本)9789819615346

Aiming at the problems of large memory space occupied by remote sensing image detection models in complex scenes, high computational complexity, and detection speed that is difficult to meet the real-time target detection requirements, a model compression algorithm based on dynamic detection head and channel pruning is proposed. Based on YOLOv5s, the head of the original YOLOv5 is replaced by the DyHead detection head, which improves the detection performance of the model by combining and unifying the three attention mechanisms of scale, space and task. Secondly, the Focaler-IoU loss function is introduced to further improve the predictive regression ability of the model. Finally, the channel pruning algorithm is used to eliminate the redundant parameters in the network to further compress the parameters and computation of the model, and the accuracy of the pruned model is improved by model fine-tuning. The experimental results show that there is a large improvement on the DOTAV1.0 dataset, and the validity is further verified on the RSOD dataset. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Jurassic

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Gray-scale transformation for traffic classification: leveraging local and global features in flow data 3

Gray-scale transformation for traffic classification: levera...

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3rd International Conference on Electronic Information engineering, Big data, and Computer Technology, EIBDCT 2024

作者： Xia, Yuchao Xue, Mutian Li, Wei Network and Data Security Key Laboratory of Sichuan Province School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu China University of Electronic Science and Technology of China Chengdu China Sichuan University of Media and Communications Chengdu China

ISBN: (纸本)9781510680449

The rapid expansion and diversification of internet traffic pose a pressing demand for accurate classification of diverse application streams in network management and security monitoring. This paper introduces a deep learning-based method for precise classification of diverse internet application streams in network. By transforming raw traffic data into grayscale images and utilizing Convolutional Neural Networks (CNNs) and the Swin-Transformer framework, critical information is extracted at both local and global feature levels. The core of this method is offering a visual representation of the structure and content of traffic data. This visual representation enables subsequent feature extraction and classification. Through experimentation across various applications including email, Skype, YouTube, Vimeo, FTP, and Facebook, the proposed method in traffic classification is demonstrated to be effective. This approach boosts traffic classification accuracy, offers innovation in network management and security monitoring, and holds vital importance in optimizing network performance and security. Additionally, it sets the stage for future research in networking data processing and security methodologies. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Network security

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Mathematical model for predicting fungal growth and decomposition rates based on improved Logistic equations

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International Journal of Agricultural and Biological engineering 2023年第1期16卷 60-65页

作者： Jiayong Pan Wenxin Le Zi’ao Wang Jian Chen College of Engineering China Agricultural UniversityBeijing 100083China Shenzhen Key Laboratory of Intelligent Microsatellite Constellation Shenzhen 518107GuangdongChina Key Laboratory of Spatial-temporal Big Data Analysis and Application of Natural Resources in Megacities MNRShanghai 200063China Key Laboratory of Urban Land Resources Monitoring and Simulation Ministry of Natural ResourcesShenzhen 518000GuangdongChina Jiangsu Province and Education Ministry Co-sponsored Synergistic Innovation Center of Modern Agricultural Equipment Jiangsu UniversityZhenjiang 212013China Key Laboratory of Smart Agricultural Technology in Tropical South China Ministry of Agriculture and Rural AffairsGuangzhou 510642China State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China State Key Laboratory of Clean Energy Utilization Zhejiang UniversityHangzhou 310013China

As the function of the decomposition of fungi has been clearly researched in the global carbon cycle,it is obviously of value to explore the decomposition rate of fungal *** study analyzed the relationship between environmental factors and biodiversity step by *** order to explore the interaction between the fungi and the relationship between the decomposition rate of fungi with time,the model based on the Logistic model was built and the Lotka-Volterra model was employed in the condition of two kinds of fungi existing in an environment with limited *** changing trend of population number and decomposition rate of several fungi under different environmental conditions can be predicted through the *** illustrate the applicability of the model,Laetiporus conifericola and Hyphoderma setigerum were applied as *** results showed that the higher the degree of population diversity,the greater the decomposition rate,and the higher the decomposition efficiency of the *** rich species diversity is conducive to accelerating the decomposition of litter,lignocellulose,and the circulation of the entire *** on the above model and using the data from measuring the mycelial elongation rate of each isolate at 10℃,16℃,and 22℃ under standardized laboratory conditions,the growth patterns of the five fungi combinations were *** results revealed a general increase in growth rate with increasing temperature,which verifies the accuracy of the ***,it also revealed that the total decomposition rate after fungal incorporation was negatively correlated with the decomposition rate of a fungal single *** on the above model,predictions can be made for fungal growth in different environments,and suitable environments for fungal growth can be *** the future,the model can be further optimized,and lignin and cellulose decomposition factors can be added to fit the decomposition of *** application

关键词： Logistic equations fungal decomposition mathematical model

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