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TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

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Journal of Iron and Steel research(International) 2024年第1期31卷 174-194页

作者： Tian-yi Xie Cai-dong Zhang Quan-lin Zhou Zhi-qiang Tian Shuai Liu Han-jie Guo Material Technology research Institute Hesteel GroupShijiazhuang050023HebeiChina Tangsteel Company Hesteel GroupTangshan063611HebeiChina School of Artificial Intelligence Beijing Technology and Business UniversityBeijing100048China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC *** maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel group steelmaking plant in China in the *** number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as ***,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time *** optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,*** field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carri

关键词： BOF steelmaking In-blow prediction TSC test Machine learning Deep learning Field application

Media Power Measuring via Emotional Contagion

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Journal of Social Computing 2024年第1期5卷 15-35页

作者： Xue Lin Hong Huang Zongya Li Hai Jin National Engineering research Center for Big data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China School of Journalism Huazhong University of Science and TechnologyWuhan 430074China

Media power,the impact that media have on public opinion and perspectives,plays a significant role in maintaining internal stability,exerting external influence,and shaping international dynamics for nations/***,prior research has primarily concentrated on news content and reporting time,resulting in limitations in evaluating media *** more accurately assess media power,we use news content,news reporting time,and news emotion simultaneously to explore the emotional contagion between *** use emotional contagion to measure the mutual influence between media and regard the media with greater impact as having stronger media *** propose a framework called Measuring Media Power via Emotional Contagion(MMPEC)to capture emotional contagion among media,enabling a more accurate assessment of media power at the media and national/regional *** also interprets experimental results through correlation and causality analyses,ensuring *** analyses confirm the higher accuracy of MMPEC compared to other baseline models,as demonstrated in the context of COVID-19-related news,yielding compelling and interesting insights.

关键词： explainability media power emotional contagion

Incense smoke(IS)inhalation exposure system:Physicochemical characterization,IS particle deposition and clearance in human airway using MPPD model

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Particuology 2024年第4期87卷 271-285页

作者： Vyas Kumar Hafsa Hashmi Anshita Nasreen Ghazi Ansari Jyotsna Singh Inhalation Toxicology Facility Regulatory Toxicology GroupCSR-Indian Institute of Toxicology ResearchLucknow22001UPIndi Academy of Scientific and Innovative research(AcsSIR) Ghaziabad201002UPIndia Analytical Chemistry Regulatory Toxicology GroupCSIR-Indian Institute of Toxicology ResearchLucknow226001UPIndia

Incense smoke(IS)is source of indoor air pollution and key risk for diverse human *** in-formation is available regarding controlled IS rodent inhalation exposure system and IS particulate matter(PM)deposition in human *** aimed to demonstrate stable ISPM physicochemical parameters of 10 incense products inside the customized whole body inhalation exposure chamber(without animal)connected to smoke generation unit via aerosol mixing *** analyzed for size segregated PM emission,ISPM in vitro aerodynamics(MMAD and GSD determination),fine and ultrafine particle's SEM,SEM-EDX and PAH *** real life exposure scenario by utilizing MMAD,GSD and PM concentration after Tier 1 exposure assessment as key input parameters,ISPM dosimetry in infant(3 months)and adult(21 years male and female)human airways was calculated using multiple-path particle dosimetry(MPPD 3.04)*** median aerodynamic diameter(MMAD)and geo-metric standard deviation(GSD)ranged between 0.55 and 2.10μm and 1.22 to 1.77(polydisperse)***1.0 and PM0.1 showed multiple morphology and presence of heavy and trace *** like acenaphthylene,anthracene,fluorene,naphthalene and phenanthrene were detected(0.84-143.17μg/g).MPPD results showed higher ISPM deposition in pulmonary region and lowest in trachea bronchial *** deposition in tissue was higher in lower,peripheral lung as compared to upper and central lung *** body inhalation exposure system showed stable IS atmosphere(physi-cochemical parameters)indicating the device suitability in future inhalation *** ISPM deposition fraction and clearance data showed deep lung penetrating and retention behavior with higher risk in infant followed by female and then *** modeled particle deposition and clearance data may be useful in risk assessment analysis of IS.

关键词： Inhalation Incense smoke Multiple-path particle dosimetry(MPPD) Particle deposition Particulate matter(PM) Mass median aerodynamic diameter (MMAD) Human airway

2D DOA Estimation of Coherent Signals with a Separated Linear Acoustic Vector-Sensor Array

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China Communications 2024年第2期21卷 155-165页

作者： Sheng Liu Jing Zhao Decheng Wu Yiwang Huang Kaiwu Luo School of data science Tongren UniversityTongren 554300China School of Automation Chongqing University of Posts and TelecommunicationsChongqing 400065China

In this paper, a two-dimensional(2D) DOA estimation algorithm of coherent signals with a separated linear acoustic vector-sensor(AVS) array consisting of two sparse AVS arrays is proposed. Firstly,the partitioned spatial smoothing(PSS) technique is used to construct a block covariance matrix, so as to decorrelate the coherency of signals. Then a signal subspace can be obtained by singular value decomposition(SVD) of the covariance matrix. Using the signal subspace, two extended signal subspaces are constructed to compensate aperture loss caused by *** elevation angles can be estimated by estimation of signal parameter via rotational invariance techniques(ESPRIT) algorithm. At last, the estimated elevation angles can be used to estimate automatically paired azimuth angles. Compared with some other ESPRIT algorithms, the proposed algorithm shows higher estimation accuracy, which can be proved through the simulation results.

关键词： acoustic vector-sensor coherent signals extended signal subspace sparse array

Mechanism and control of nonuniform phase transformation of microalloyed dual-phase steel during cooling process after hot rolling

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Journal of Iron and Steel research(International) 2024年第2期31卷 428-441页

作者： Wen-quan Sun Sheng-yi Yong Tie-heng Yuan Chao Liu San-bao Zhou Rui-chun Guo Meng-xia Tang National Engineering research Center for Advanced Rolling and Intelligent Manufacturing University of Science and Technology BeijingBeijing100083China Strip Production Plant Xichang Steel and Vanadium Corporation of Pangang GroupXichang615000SichuanChina

After cooling in the hot rolling process,the metallographic structure of microalloyed dual-phase steel is nonuniform along the rolling direction,while the thickness fluctuation of microalloyed dual-phase steel with a nonuniform metallographic structure will occur during cold *** mechanism of nonuniform phase transformation of microalloyed dual-phase steels was studied during the cooling process after hot rolling,and the nonuniform phase transformation of microalloyed dual-phase steel was regulated during the cooling process after hot rolling through process ***,the empirical equation of phase transformation temperature was measured by a dilatometer considering thermal ***,the phase field and temperature field of laminar cooling process were calculated to provide initial boundary conditions for the finite element *** that,the coupling finite element model of the temperature phase transformation of the strip steel in coiling transportation process was *** simulation results show that the different thermal contact conditions of the microalloyed dual-phase steel during coil transportation lead to uneven cooling of the coil,which leads to nonuniform transformation of the coil along the rolling *** addition,by prolonging the time interval from coiling to unloading,the phenomenon of nonuniform phase transformation of microalloyed dual-phase steel can be effectively *** simulation results are applied to industrial *** application results show that prolonging the time interval from coiling to unloading can effectively improve the nonuniform phase transformation of microalloyed dual-phase steel in the cooling process after hot rolling.

关键词： Microalloyed dual-phase steel Thickness fluctuation Cooling Heat conduction Nonuniform phase transition Finite element method

XRL-SHAP-Cache:an explainable reinforcement learning approach for intelligent edge service caching in content delivery networks

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science China(Information sciences) 2024年第7期67卷 46-71页

作者： Xiaolong XU Fan WU Muhammad BILAL Xiaoyu XIA Wanchun DOU Lina YAO Weiyi ZHONG School of Software Nanjing University of Information Science and Technology School of Computing and Communications Lancaster University School of Computing Technologies Royal Melbourne Institute of Technology State Key Laboratory for Novel Software Technology Nanjing University School of Computer science and Engineering University of New South Wales data 61 Commonwealth Scientific and Industrial Research Organization School of Computer science Qufu Normal University

Content delivery networks(CDNs) play a pivotal role in the modern internet infrastructure by enabling efficient content delivery across diverse geographical regions. As an essential component of CDNs, the edge caching scheme directly influences the user experience by determining the caching and eviction of content on edge servers. With the emergence of 5G technology, traditional caching schemes have faced challenges in adapting to increasingly complex and dynamic network environments. Consequently, deep reinforcement learning(DRL) offers a promising solution for intelligent zero-touch network governance. However, the blackbox nature of DRL models poses challenges in understanding and making trusting decisions. In this paper,we propose an explainable reinforcement learning(XRL)-based intelligent edge service caching approach,namely XRL-SHAP-Cache, which combines DRL with an explainable artificial intelligence(XAI) technique for cache management in CDNs. Instead of focusing solely on achieving performance gains, this study introduces a novel paradigm for providing interpretable caching strategies, thereby establishing a foundation for future transparent and trustworthy edge caching solutions. Specifically, a multi-level cache scheduling framework for CDNs was formulated theoretically, with the D3QN-based caching scheme serving as the targeted interpretable model. Subsequently, by integrating Deep-SHAP into our framework, the contribution of each state input feature to the agent's Q-value output was calculated, thereby providing valuable insights into the decision-making process. The proposed XRL-SHAP-Cache approach was evaluated through extensive experiments to demonstrate the behavior of the scheduling agent in the face of different environmental *** results demonstrate its strong explainability under various real-life scenarios while maintaining superior performance compared to traditional caching schemes in terms of cache hit ratio, quality of service(QoS),a

关键词： deep reinforcement learning (DRL) explainable artificial intelligence (XAI) multi-level cache content delivery network (CDN) D3QN algorithm Deep-SHAP

IQABC-Based Hybrid Deployment Algorithm for Mobile Robotic Agents Providing Network Coverage

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Tsinghua science and Technology 2024年第2期29卷 589-604页

作者： Shuang Xu Xiaojie Liu Dengao Li Jumin Zhao College of Computer science and Technology(College of data science) Taiyuan University of TechnologyTaiyuan 030024China Pengcheng Laboratory Shenzhen 518055China College of Information and Computer Taiyuan University of TechnologyTaiyuan 030024China

Working as aerial base stations,mobile robotic agents can be formed as a wireless robotic network to provide network services for on-ground mobile devices in a target ***,a challenging issue is how to deploy these mobile robotic agents to provide network services with good quality for more users,while considering the mobility of on-ground *** this paper,to solve this issue,we decouple the coverage problem into the vertical dimension and the horizontal dimension without any loss of optimization and introduce the network coverage model with maximum coverage ***,we propose a hybrid deployment algorithm based on the improved quick artificial bee *** algorithm is composed of a centralized deployment algorithm and a distributed *** proposed deployment algorithm deploy a given number of mobile robotic agents to provide network services for the on-ground devices that are independent and identically *** results have demonstrated that the proposed algorithm deploys agents appropriately to cover more ground area and provide better coverage uniformity.

关键词： wireless robotic networks network coverage deployment algorithm improved quick artificial bee colony

Enhancing Offensive Language Detection with data Augmentation and Knowledge Distillation

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research 2024年第2期6卷 29-40页

作者： Jiawen Deng Zhuang Chen Hao Sun Zhexin Zhang Jincenzi Wu Satoshi Nakagawa Fuji Ren Minlie Huang The CoAl group DCSTInstitute for Artificial InteligenceState Key Lab of Intelligent Technology and SystemsBeijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing 100084China Graduate School of Information science&Technology The University of Tokyo.Tokyo 1138654Japan School of Computer science and Engineering University of Electronic Science and Technology of ChinaChengduSichuan611731China

Offensive language detection has received important attention and plays a crucial role in promoting healthy communication on social platforms,as well as promoting the safe deployment of large language *** data is the basis for developing detectors;however,the available offense-related dataset in Chinese is severely limited in terms of data scale and coverage when compared to English *** significantly affects the accuracy of Chinese offensive language detectors in practical applications,especially when dealing with hard cases or out-of-domain *** alleviate the limitations posed by available datasets,we introduce AugCOLD(Augmented Chinese Offensive Language dataset),a large-scale unsupervised dataset containing 1 million samples gathered by data crawling and model ***,we employ a multiteacher distillation framework to enhance detection performance with unsupervised *** is,we build multiple teachers with publicly accessible datasets and use them to assign soft labels to *** soft labels serve as a bridge for knowledge to be distilled from both AugCOLD and multiteacher to the student network,i.e.,the final offensive *** conduct experiments on multiple public test sets and our well-designed hard tests,demonstrating that our proposal can effectively improve the generalization and robustness of the offensive language detector.

关键词： COLD dealing limitations

Inter-layer interference for multi-layered tight gas reservoir in the absence and presence of movable water

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Petroleum science 2024年第3期21卷 1751-1764页

作者： Tao Zhang Bin-Rui Wang Yu-Long Zhao Lie-Hui Zhang Xiang-Yang Qiao Lei Zhang Jing-Jing Guo Hung Vo Thanh National Key Laboratory of Oil and Gas Reservoir Geology and Exploitation Southwest Petroleum University Shaanxi Yanchang Petroleum (group) Corp.Ltd. Waseda research Institute for science and Engineering Waseda University

Due to the dissimilarity among different producing layers, the influences of inter-layer interference on the production performance of a multi-layer gas reservoir are possible. However, systematic studies of inter-layer interference for tight gas reservoirs are really limited, especially for those reservoirs in the presence of water. In this work, five types of possible inter-layer interferences, including both absence and presence of water, are identified for commingled production of tight gas reservoirs. Subsequently, a series of reservoir-scale and pore-scale numerical simulations are conducted to quantify the degree of influence of each type of interference. Consistent field evidence from the Yan'an tight gas reservoir(Ordos Basin, China) is found to support the simulation results. Additionally, suggestions are proposed to mitigate the potential inter-layer interferences. The results indicate that, in the absence of water, commingled production is favorable in two situations: when there is a difference in physical properties and when there is a difference in the pressure system of each layer. For reservoirs with a multi-pressure system, the backflow phenomenon, which significantly influences the production performance, only occurs under extreme conditions(such as very low production rates or well shut-in periods). When water is introduced into the multi-layer system, inter-layer interference becomes nearly *** both the gas-rich layer and water-rich layer for commingled production is not desirable, as it can trigger water invasion from the water-rich layer into the gas-rich layer. The gas-rich layer might also be interfered with by water from the neighboring unperforated water-rich layer, where the water might break the barrier(eg weak joint surface, cement in fractures) between the two layers and migrate into the gas-rich layer. Additionally, the gas-rich layer could possibly be interfered with by water that accumulates at the bottom of the we

关键词： Tight gas Comingled production Interference Two-phase flow Water blocking