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Interpretable Machine Learning Method for Compressive Strength Prediction and Analysis of Pure Fly Ash-based Geopolymer Concrete

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 65-78页

作者： SHI Yuqiong LI Jingyi ZHANG Yang LI Li Key Laboratory of Agricultural Soil and Water engineering in Arid and Semiarid Areas of Ministry of Education Northwest A&F Uni-versityYangling 712100China College of Water Resources and Architectural engineering Northwest A&F UniversityYangling 712100China Chongqing Key Laboratory of Public Big Data Security Technology Chongqing 401420China Chongqing College of Mobile Communication Chongqing 401520China department of civil and Environmental engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina National Rail Transit Electrification and Automation engineering Technology Research Center(Hong Kong Branch) The Hong Kong Polytechnic UniversityKowloonHung HomHong KongChina

In order to study the characteristics of pure fly ash-based geopolymer concrete(PFGC)conveniently,we used a machine learning method that can quantify the perception of characteristics to predict its compressive *** this study,505 groups of data were collected,and a new database of compressive strength of PFGC was *** order to establish an accurate prediction model of compressive strength,five different types of machine learning networks were used for comparative *** five machine learning models all showed good compressive strength prediction performance on *** them,R2,MSE,RMSE and MAE of decision tree model(DT)are 0.99,1.58,1.25,and 0.25,*** R2,MSE,RMSE and MAE of random forest model(RF)are 0.97,5.17,2.27 and 1.38,*** two models have high prediction accuracy and outstanding generalization *** order to enhance the interpretability of model decision-making,we used importance ranking to obtain the perception of machine learning model to 13 *** 13 variables include chemical composition of fly ash(SiO_(2)/Al_(2)O_(3),Si/Al),the ratio of alkaline liquid to the binder,curing temperature,curing durations inside oven,fly ash dosage,fine aggregate dosage,coarse aggregate dosage,extra water dosage and sodium hydroxide *** temperature,specimen ages and curing durations inside oven have the greatest influence on the prediction results,indicating that curing conditions have more prominent influence on the compressive strength of PFGC than ordinary Portland cement *** importance of curing conditions of PFGC even exceeds that of the concrete mix proportion,due to the low reactivity of pure fly ash.

关键词： machine learning pure fly ash geopolymer compressive strength feature perception

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Steel Surface Defect Detection Using Learnable Memory Vision Transformer

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Computers, Materials & Continua 2025年第1期82卷 499-520页

作者： Syed Tasnimul Karim Ayon Farhan Md.Siraj Jia Uddin department of Computer Science and engineering BRAC UniversityDhaka1212Bangladesh department of AI and Big Data Endicott CollegeWoosong UniversityDaejeon34606Republic of Korea

This study investigates the application of Learnable Memory Vision Transformers(LMViT)for detecting metal surface flaws,comparing their performance with traditional CNNs,specifically ResNet18 and ResNet50,as well as other transformer-based models including Token to Token ViT,ViT withoutmemory,and Parallel *** awidely-used steel surface defect dataset,the research applies data augmentation and t-distributed stochastic neighbor embedding(t-SNE)to enhance feature extraction and *** techniques mitigated overfitting,stabilized training,and improved generalization *** LMViT model achieved a test accuracy of 97.22%,significantly outperforming ResNet18(88.89%)and ResNet50(88.90%),aswell as the Token to TokenViT(88.46%),ViT without memory(87.18),and Parallel ViT(91.03%).Furthermore,LMViT exhibited superior training and validation performance,attaining a validation accuracy of 98.2%compared to 91.0%for ResNet 18,96.0%for ResNet50,and 89.12%,87.51%,and 91.21%for Token to Token ViT,ViT without memory,and Parallel ViT,*** findings highlight the LMViT’s ability to capture long-range dependencies in images,an areawhere CNNs struggle due to their reliance on local receptive fields and hierarchical feature *** additional transformer-based models also demonstrate improved performance in capturing complex features over CNNs,with LMViT excelling particularly at detecting subtle and complex defects,which is critical for maintaining product quality and operational efficiency in industrial *** instance,the LMViT model successfully identified fine scratches and minor surface irregularities that CNNs often *** study not only demonstrates LMViT’s potential for real-world defect detection but also underscores the promise of other transformer-based architectures like Token to Token ViT,ViT without memory,and Parallel ViT in industrial scenarios where complex spatial relationships are *** research m

关键词： Learnable Memory Vision Transformer(LMViT) Convolutional Neural Networks(CNN) metal surface defect detection deep learning,computer vision image classification learnable memory gradient clipping label smoothing t-SNE visualization

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Review of Techniques for Integrating Security in Software Development Lifecycle

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Computers, Materials & Continua 2025年第1期82卷 139-172页

作者： Hassan Saeed Imran Shafi Jamil Ahmad Adnan Ahmed Khan Tahir Khurshaid Imran Ashraf College of Electrical and Mechanical engineering National University of Sciences and Technology(NUST)Rawalpindi46604Pakistan department of Computer Science Abasyn University Islamabad CampusIslamabad45510Pakistan Military College of Signals National University of Sciences and Technology(NUST)Rawalpindi46600Pakistan department of Electrical engineering Yeungnam UniversityGyeongsan38541Republic of Korea department of Information and Communication engineering Yeungnam UniversityGyeongsan38541Republic of Korea

Software-related security aspects are a growing and legitimate concern,especially with 5G data available just at our *** conduct research in this field,periodic comparative analysis is needed with the new techniques coming up *** purpose of this study is to review the recent developments in the field of security integration in the software development lifecycle(SDLC)by analyzing the articles published in the last two decades and to propose a way *** review follows Kitchenham’s review *** review has been divided into three main stages including planning,execution,and *** the selected 100 articles,it becomes evident that need of a collaborative approach is necessary for addressing critical software security risks(CSSRs)through effective risk management/estimation *** risks using a numeric scale enables a comprehensive understanding of their severity,facilitating focused resource allocation and mitigation *** a comprehensive understanding of potential vulnerabilities and proactive mitigation efforts facilitated by protection poker,organizations can prioritize resources effectively to ensure the successful outcome of projects and initiatives in today’s dynamic threat *** review reveals that threat analysis and security testing are needed to develop automated tools for the *** estimation of effort required to prioritize potential security risks is a big challenge in software *** accuracy of effort estimation can be further improved by exploring new techniques,particularly those involving deep *** is also imperative to validate these effort estimation methods to ensure all potential security threats are *** challenge is selecting the right model for each specific security *** achieve a comprehensive evaluation,researchers should use well-known benchmark checklists.

关键词： Software development lifecycle systematic literature review critical software security risks national institute of standards and technology DevSecOps open web application security project McGraw’s touch points

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Situation-adaptive neural network for fast pre-computing image enhancement

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Science China(Information Sciences) 2025年

作者： Xinyue LI Huiyu DUAN Jia WANG Xiaohong LIU Yitong CHEN Guangtao ZHAI Institute of Image Communication and Network engineering Department of Electronic EngineeringShanghai Jiao Tong University

As intelligent vision tasks become more widespread, enhancing image quality before further computational analysis is crucial. Recently, deep learning has shown potential for automated pre-computing enhancement, but it typically requires substantial computational resources and is hard to adapt to in multiple situations without *** practice, image enhancement often demands flexible adjustments based on different situations and subsequent computation devices, such as optical computing. Therefore,we propose SAEnhancer, a situation-adaptive neural network for fast pre-computing image enhancement. It learns from a small sample set to achieve personalized and adaptive enhancements for various situations without re-training,using semantic-aware embedding for precise color adjustments, surpassing traditional 3D lookup tables (LUTs), and enhancing computational effectiveness in intelligent vision applications.

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Targets capture by distributed active swarms via bio-inspired reinforcement learning

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Science China(Physics,Mechanics & Astronomy) 2025年第1期Mechanics & Astronomy) .卷 210-221页

作者： Kun Xu Yue Li Jun Sun Shuyuan Du Xinpeng Di Yuguang Yang Bo Li Institute of Biomechanics and Medical engineering Applied Mechanics Laboratory Department of Engineering MechanicsTsinghua University Institute of Nuclear and New Energy Technology Tsinghua University Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology College of Automation engineering Nanjing University of Aeronautics and Astronautics

Natural swarms arranged from cells to herds are usually decentralized but display intriguing collective intelligence in coordinating individuals across large scales to efficiently achieve their common goals. Learning from nature may provide new strategies for controlling collective dynamics of synthetic swarms to accomplish specific functions. Here, we present a bioinspired computational framework that steers distributed active swarms to collectively capture and merge targets via reinforcement learning. We exploit collective milling structures of natural herds to cage the targets, and adopt a switching control policy inspired by sperms' chiral dynamics to optimize the trajectories of individuals, through which the active swarms can selforganize to enclose single or multiple distant targets in a dynamical, adaptive and scalable manner. There exists a critical swarm size, beyond which the excessive competition between agents would generate large mechanical forces, leading to capture instability but enabling the transition from short-distance to long-distance merging capture of multiple targets. This work provides physical insights into distributed active swarms and could offer a multilevel, decentralized strategy toward controlling swarm robotics in wide applications such as bio-medical devices, machine immunity, and target clearance.

关键词： swarm intelligence robotics multi-tasks artificial intelligence bionics

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Emerging trends in the selective production of value-added aromatics

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Science China Chemistry 2025年第1期68卷 15-20页

作者： Yuchao Wu Houliang Dai Weisheng Yang Yaxing Li Lichen Liu Petrochemical Research Institute Company Limited China National Petroleum Corporation engineering Research Center of Advanced Rare Earth Materials Department of Chemistry Tsinghua University

1 Introduction Aromatics (mainly benzene, toluene, and xylenes, BTX) are essential intermediates in the chemical industry. They are employed in the synthesis of a broad spectrum of chemicals and materials, e.g., various polymers, plastics, resins, solvents, dyes, pharmaceuticals [1]. The manufacturing pathway of BTX mainly includes petroleum reforming of naphtha, coal-to-aromatics, methanol-to-aromatics [2].

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Intrumer:A Multi Module Distributed Explainable IDS/IPS for Securing Cloud Environment

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Computers, Materials & Continua 2025年第1期82卷 579-607页

作者： Nazreen Banu A S.K.B.Sangeetha department of Computer Science and engineering SRM Institute of Science and TechnologyVadapalani CampusChennai600026Tamil NaduIndia

The increasing use of cloud-based devices has reached the critical point of cybersecurity and unwanted network *** environments pose significant challenges in maintaining privacy and *** approaches,such as IDS,have been developed to tackle these ***,most conventional Intrusion Detection System(IDS)models struggle with unseen cyberattacks and complex high-dimensional *** fact,this paper introduces the idea of a novel distributed explainable and heterogeneous transformer-based intrusion detection system,named INTRUMER,which offers balanced accuracy,reliability,and security in cloud settings bymultiplemodulesworking together within *** traffic captured from cloud devices is first passed to the TC&TM module in which the Falcon Optimization Algorithm optimizes the feature selection process,and Naie Bayes algorithm performs the classification of *** selected features are classified further and are forwarded to the Heterogeneous Attention Transformer(HAT)*** this module,the contextual interactions of the network traffic are taken into account to classify them as normal or malicious *** classified results are further analyzed by the Explainable Prevention Module(XPM)to ensure trustworthiness by providing interpretable *** the explanations fromthe classifier,emergency alarms are transmitted to nearby IDSmodules,servers,and underlying cloud devices for the enhancement of preventive *** experiments on benchmark IDS datasets CICIDS 2017,Honeypots,and NSL-KDD were conducted to demonstrate the efficiency of the INTRUMER model in detecting network trafficwith high accuracy for different *** outperforms state-of-the-art approaches,obtaining better performance metrics:98.7%accuracy,97.5%precision,96.3%recall,and 97.8%*** results validate the robustness and effectiveness of INTRUMER in securing diverse cloud environments against sophisticated cyber threats.

关键词： Cloud computing intrusion detection system transformers and explainable artificial intelligence(XAI)

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Dynamic Interaction Analysis of Coupled Axial-Torsional-Lateral Mechanical Vibrations in Rotary Drilling Systems

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Structural Durability & Health Monitoring 2025年第1期19卷 77-103页

作者： Sabrina Meddah Sid Ahmed Tadjer Abdelhakim Idir Kong Fah Tee Mohamed Zinelabidine Doghmane Madjid Kidouche Applied Automation Laboratory Faculty of Hydrocarbons and ChemistryUniversity of BoumerdesBoumerdes35000Algeria Institute of Electrical and Electronic engineering(IGEE) University of BoumerdesBoumerdes35000Algeria Laboratory of the Electrification of Industrial Enterprises University of BoumerdesBoumerdes35000Algeria Electrical engineering department Mohamed Boudiaf University of M’silaM’sila28000Algeria department of civil and Environmental engineering King Fahd University of Petroleum&MineralsDhahran31261Saudi Arabia Interdisciplinary Research Center for Construction and Building Materials King Fahd University of Petroleum&Minerals(KFUPM)Dhahran31261Saudi Arabia

Maintaining the integrity and longevity of structures is essential in many industries,such as aerospace,nuclear,and *** achieve the cost-effectiveness of large-scale systems in petroleum drilling,a strong emphasis on structural durability and monitoring is *** study focuses on the mechanical vibrations that occur in rotary drilling systems,which have a substantial impact on the structural integrity of drilling *** study speciﬁcally investigates axial,torsional,and lateral vibrations,which might lead to negative consequences such as bit-bounce,chaotic whirling,and high-frequency *** events not only hinder the efﬁciency of drilling but also lead to exhaustion and harm to the system’s components since they are difﬁcult to be detected and controlled in real *** study investigates the dynamic interactions of these vibrations,speciﬁcally in their high-frequency modes,usingﬁeld data obtained from measurement while ***ﬁndings have demonstrated the effect of strong coupling between the high-frequency modes of these vibrations on drilling sys-tem *** obtained results highlight the importance of considering the interconnected impacts of these vibrations when designing and implementing robust control ***,integrating these compo-nents can increase the durability of drill bits and drill strings,as well as improve the ability to monitor and detect ***,by exploiting theseﬁndings,the assessment of structural resilience in rotary drilling systems can be ***,the study demonstrates the capacity of structural health monitoring to improve the quality,dependability,and efﬁciency of rotary drilling systems in the petroleum industry.

关键词： Rotary drilling systems mechanical vibrations structural durability dynamic interaction analysis ﬁeld data analysis

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Preparation and Performance of Ternary Early Strength Agent and Quercetin Composite Cement Sealing Material

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Journal of Wuhan University of Technology(Materials Science) 2025年第1期40卷 130-140页

作者： LIU Jian CHEN Meiting JI Xiaoli XU Chao WANG Chunmei department of Safety Science and engineering Anhui University of Science and TechnologyHuainan 232001China Key Laboratory of Mine Safety and High Efficient Mining Jointly Built by Province and Education Ministry Anhui University of Science and TechnologyHuainan 232001China department of Chemical engineering and Explosives Anhui University of Science and TechnologyHuainan 232001China

A ternary early-strengthening agent consisting of calcium formate+triethanolamine+lithium sulfate was compounded with quercetin to shorten the setting time of cementitious materials while ensuring their early *** optimum ratio of the three early-strengthening agents was determined as 0.5%calcium formate+0.04%triethanolamine+0.4%lithium sulfate by response surface *** effects of the ternary early-strengthening agent composed of calcium formate+triethanolamine(TEA)+lithium sulfate on cementitious pore sealing materials under the synergistic effect of quercetin were studied by means of the performance tests of compressive strength,fluidity,and setting time,and the microstructural characterizations of X-ray powder diffractometer(XRD),thermogravimetry(TG-DSC)and scanning electron microscopy(SEM).The study shows that the synergistic effect of ternary early-strengthening agent and quercetin forms a multi-performance composite admixture for cementitious *** best performance was obtained with the compounding scheme of 0.5%calcium formate+0.04%triethanolamine+0.4%lithium sulfate ternary early-strengthening agent and 0.05%*** compressive strength of 1,3,7,and 28 d are 94.8%,39.8%,42%,and 28%higher than those of the blank group,*** initial time and final setting time are 41 and 57 minutes,*** to the microscopic analysis,the network and fibrous C-S-H gels generated by ternary early-strengthening agents are attached to the surface promoted by quercetin,which forms skeleton support while thickening and solidifying the cement slurry,which enhances the early compressive strength of the cement-based materials.

关键词： sealing material ternary early-strengthening agent quercetin synergetic effect response surface methodology

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Enhanced solid-electrolyte interface efficiency for practically viable hydrogen-air fuel cell systems

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Journal of Energy Chemistry 2025年第1期100卷 356-368页

作者： Venkitesan Sakthivel Dong Jin Yoo Graduate School Department of Energy Storage/Conversion Engineering (BK21 FOUR) Hydrogen and Fuel Cell Research Center Jeonbuk National University Jeonju department of Life Science Jeonbuk National University

Proton exchange membrane fuel cells （PEMFCs） provide an appealing sustainable energy system,with the solid-electrolyte membrane playing a crucial role in its overall ***,sulfonated poly（1,4-phenylene ether-ether sulfone）(SPEES),an aromatic hydrocarbon polymer,has garnered considerable attention as an alternative to Nafion ***,the long-term durability and stability of SPEES present a significant *** this context,we introduce a potential solution in the form of an additive,specifically a core–shell-based amine-functionalized iron titanate （A–Fe2TiO5）,which holds promise for improving the lifetime,proton conductivity,and power density of SPEES in *** modified SPEES/A–Fe2TiO5composite membranes exhibited notable characteristics,including high water uptake,enhanced thermomechanical stability,and oxidative ***,the SPEES membrane loaded with 1.2 wt%of A–Fe2TiO5demonstrates a maximum proton conductivity of 155 mS cm-1,a twofold increase compared to the SPEES membrane,at 80°C under 100%relative humidity （RH）.Furthermore,the 1.2 wt%of A–Fe2TiO5/SPEES composite membranes exhibited a maximum power density of 397.37 mW cm-2and a current density of 1148 mA cm-2at 60°C under 100%RH,with an opencircuit voltage decay of 0.05 m V/h during 103 h of continuous *** study offers significant insights into the development and understanding of innovative SPEES nanocomposite membranes for PEMFC applications.

关键词： Composite membranes

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