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Atmospheric oxidation capacity and O_(3) formation in a coastal city of southeast China:Results from simulation based on four-season observation

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Journal of Environmental Sciences 2024年第2期136卷 68-80页

作者： Gaojie Chen Taotao Liu Jinsheng Chen Lingling xu Baoye Hu Chen Yang xiaolong Fan Mengren Li Youwei Hong Xiaoting Ji Jinfang Chen Fuwang Zhang Center for Excellence in Regional Atmospheric Environment Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China Key Lab of Urban Environment and Health Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China University of Chinese Academy of Sciences Beijing 100049China Minnan Normal University Zhangzhou 363000China College of Harbour and Coastal Engineering Jimei UniversityXiamen 361021China Environmental Monitoring Center of Fujian Fuzhou 350013China

The pollution of atmospheric ozone in China shows an obvious upward trend in the past decade.However,the studies on the atmospheric oxidation capacity and O_(3)formation in four seasons in the southeastern coastal region of China with the rapid urbanization remain limited.Here,a four-season field observation was carried out in a coastal city of southeast China,using an observation-based model combining with the Master Chemical Mechanism,to explore the atmospheric oxidation capacity(AOC),radical chemistry,O_(3)formation pathways and sensitivity.The results showed that the average net O_(3)production rate(14.55 ppbv/hr)in summer was the strongest,but the average O_(3)concentrations in autumn was higher.The AOC and ROx levels presented an obvious seasonal pattern with the maximum value in summer,while the OH reactivity in winter was the highest with an average value of 22.75 sec^(-1).The OH reactivity was dominated by oxygenated VOCs(OVOCs)(30.6%-42.8%),CO(23.2%-26.8%),NO_(2)(13.6%-22.0%),and alkenes(8.4%-12.5%)in different seasons.HONO photolysis dominated OH primary source on daytime in winter,while in other seasons,HONO photolysis in the morning and ozone photolysis in the afternoon contributed mostly.Sensitivity analysis indicated that O_(3)production was controlled by VOCs in spring,autumn and winter,but a VOC-limited and NOx-limited regime in summer,and alkene and aromatic species were the major controlling factors to O_(3)formation.Overall,the study characterized the atmospheric oxidation capacity and elucidated the controlling factors for O_(3)production in the coastal area with the rapid urbanization in China.

关键词： Atmospheric oxidation capacity Radical chemistry Ozone production Sensitivity analysis

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A Review of the Current Task Offloading Algorithms,Strategies and Approach in Edge Computing Systems

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工程与科学中的计算机建模（英文） 2023年第1期134卷 35-88页

作者： Abednego Acheampong Yiwen Zhang xiaolong xu Daniel Appiah Kumah School of Computer Science and Technology Anhui UniversityHefei230039China School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China

Task offloading is an important concept for edge computing and the Internet of Things(IoT)because computationintensive tasksmust beoffloaded tomore resource-powerful remote devices.Taskoffloading has several advantages,including increased battery life,lower latency,and better application performance.A task offloading method determines whether sections of the full application should be run locally or offloaded for execution remotely.The offloading choice problem is influenced by several factors,including application properties,network conditions,hardware features,and mobility,influencing the offloading system’s operational environment.This study provides a thorough examination of current task offloading and resource allocation in edge computing,covering offloading strategies,algorithms,and factors that influence offloading.Full offloading and partial offloading strategies are the two types of offloading strategies.The algorithms for task offloading and resource allocation are then categorized into two parts:machine learning algorithms and non-machine learning algorithms.We examine and elaborate on algorithms like Supervised Learning,Unsupervised Learning,and Reinforcement Learning(RL)under machine learning.Under the non-machine learning algorithm,we elaborate on algorithms like non(convex)optimization,Lyapunov optimization,Game theory,Heuristic Algorithm,Dynamic Voltage Scaling,Gibbs Sampling,and Generalized Benders Decomposition(GBD).Finally,we highlight and discuss some research challenges and issues in edge computing.

关键词： Task offloading machine learning algorithm game theory dynamic voltage scaling

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Precise orbit determination for BDS satellites

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Satellite Navigation 2022年第1期3卷 1-24,I0002页

作者： Qile Zhao Jing Guo Chen Wang Yifei Lyu xiaolong xu Chao Yang Junqiang Li GNSS Research Center Wuhan University129 Luoyu RoadWuhan 430079China School of Geological Engineering and Geomatics 126 Yanta RoadXi’an 710064China School of Geodesy and Geomatics Wuhan University129 Luoyu RoadWuhan 430079China.

Since the frst pair of BeiDou satellites was deployed in 2000,China has made continuous eforts to establish its own independent BeiDou Navigation Satellite System(BDS)to provide the regional radio determination satellite service as well as regional and global radio navigation satellite services,which rely on the high quality of orbit and clock products.This article summarizes the achievements in the precise orbit determination(POD)of BDS satellites in the past decade with the focus on observation and orbit dynamic models.First,the disclosed metadata of BDS satellites is presented and the contribution to BDS POD is addressed.The complete optical properties of the satellite bus as well as solar panels are derived based on the absorbed parameters as well the material properties.Secondly,the status and tracking capabilities of the L-band data from accessible ground networks are presented,while some low earth orbiter satellites with onboard BDS tracking capability are listed.The topological structure and measurement scheme of BDS Inter-Satellite-Link(ISL)data are described.After highlighting the progress on observation models as well as orbit perturbations for BDS,e.g.,phase center corrections,satellite attitude,and solar radiation pressure,diferent POD strategies used for BDS are summarized.In addition,the urgent requirement for error modeling of the ISL data is emphasized based on the analysis of the observation noises,and the incompatible characteristics of orbit and clock derived with L-band and ISL data are illuminated and discussed.The further researches on the improvement of phase center calibration and orbit dynamic models,the refnement of ISL observation models,and the potential contribution of BDS to the estimation of geodetic parameters based on L-band or ISL data are identifed.With this,it is promising that BDS can achieve better performance and provides vital contributions to the geodesy and navigation.

关键词： BDS Orbit and clock Solar radiation pressure Attitude Phase center correction Inter-satellite-link

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Corpus of Carbonate Platforms with Lexical Annotations for Named Entity Recognition

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Computer Modeling in Engineering & Sciences 2023年第4期135卷 91-108页

作者： Zhichen Hu Huali Ren Jielin Jiang Yan Cui Xiumian Hu xiaolong xu School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Institution of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou515021China School of Earth Sciences and Engineering Nanjing UniversityNanjing210023China College of Mathematics and Information Science Nanjing Normal University of Special EducationNanjing210023China

An obviously challenging problem in named entity recognition is the construction of the kind data set of entities.Although some research has been conducted on entity database construction,the majority of them are directed at Wikipedia or the minority at structured entities such as people,locations and organizational nouns in the news.This paper focuses on the identification of scientific entities in carbonate platforms in English literature,using the example of carbonate platforms in sedimentology.Firstly,based on the fact that the reasons for writing literature in key disciplines are likely to be provided by multidisciplinary experts,this paper designs a literature content extraction method that allows dealing with complex text structures.Secondly,based on the literature extraction content,we formalize the entity extraction task(lexicon and lexical-based entity extraction)for entity extraction.Furthermore,for testing the accuracy of entity extraction,three currently popular recognition methods are chosen to perform entity detection in this paper.Experiments show that the entity data set provided by the lexicon and lexical-based entity extraction method is of significant assistance for the named entity recognition task.This study presents a pilot study of entity extraction,which involves the use of a complex structure and specialized literature on carbonate platforms in English.

关键词： Named entity recognition carbonate platform corpus entity extraction english literature detection

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Data Masking for Chinese Electronic Medical Records with Named Entity Recognition

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Intelligent Automation & Soft Computing 2023年第6期36卷 3657-3673页

作者： Tianyu He xiaolong xu Zhichen Hu Qingzhan Zhao Jianguo Dai Fei Dai School of Computer Science Nanjing University of Information Science and TechnologyNanjing21000China Geospatial Information Engineering Research Center Xinjiang Production and Construction CorpsShihezi832003China College of Big Data and Intelligent Engineering Southwest Forestry UniversityKunming650224China

With the rapid development of information technology,the electronifi-cation of medical records has gradually become a trend.In China,the population base is huge and the supporting medical institutions are numerous,so this reality drives the conversion of paper medical records to electronic medical records.Electronic medical records are the basis for establishing a smart hospital and an important guarantee for achieving medical intelligence,and the massive amount of electronic medical record data is also an important data set for conducting research in the medical field.However,electronic medical records contain a large amount of private patient information,which must be desensitized before they are used as open resources.Therefore,to solve the above problems,data masking for Chinese electronic medical records with named entity recognition is proposed in this paper.Firstly,the text is vectorized to satisfy the required format of the model input.Secondly,since the input sentences may have a long or short length and the relationship between sentences in context is not negligible.To this end,a neural network model for named entity recognition based on bidirectional long short-term memory(BiLSTM)with conditional random fields(CRF)is constructed.Finally,the data masking operation is performed based on the named entity recog-nition results,mainly using regular expression filtering encryption and principal component analysis(PCA)word vector compression and replacement.In addi-tion,comparison experiments with the hidden markov model(HMM)model,LSTM-CRF model,and BiLSTM model are conducted in this paper.The experi-mental results show that the method used in this paper achieves 92.72%Accuracy,92.30%Recall,and 92.51%F1_score,which has higher accuracy compared with other models.

关键词： Named entity recognition Chinese electronic medical records data masking principal component analysis regular expression

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Person Re-Identification with Model-Contrastive Federated Learning in Edge-Cloud Environment

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Intelligent Automation & Soft Computing 2023年第10期38卷 35-55页

作者： Baixuan Tang xiaolong xu Fei Dai Song Wang School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science and TechnologyNanjing210044China School of Big Data and Intelligence Engineering Southwest Forestry UniversityKunming650233China Nanjing Meteorological Service Center Nanjing Meteorological BureauNanjing210019China

Person re-identification(ReID)aims to recognize the same person in multiple images from different camera views.Training person ReID models are time-consuming and resource-intensive;thus,cloud computing is an appropriate model training solution.However,the required massive personal data for training contain private information with a significant risk of data leakage in cloud environments,leading to significant communication overheads.This paper proposes a federated person ReID method with model-contrastive learning(MOON)in an edge-cloud environment,named FRM.Specifically,based on federated partial averaging,MOON warmup is added to correct the local training of individual edge servers and improve the model’s effectiveness by calculating and back-propagating a model-contrastive loss,which represents the similarity between local and global models.In addition,we propose a lightweight person ReID network,named multi-branch combined depth space network(MB-CDNet),to reduce the computing resource usage of the edge device when training and testing the person ReID model.MB-CDNet is a multi-branch version of combined depth space network(CDNet).We add a part branch and a global branch on the basis of CDNet and introduce an attention pyramid to improve the performance of the model.The experimental results on open-access person ReID datasets demonstrate that FRM achieves better performance than existing baseline.

关键词： Person re-identification federated learning contrastive learning

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Malicious code passive propagation model and vaccine distribution model of P2P networks

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Journal of Systems Engineering and Electronics 2010年第1期21卷 161-167页

作者： xiaolong xu Ruchuan Wang Fu Xiao School of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 E R. China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 P. R. China

To fight against malicious codes of P2P networks, it is necessary to study the malicious code propagation model of P2P networks in depth. The epidemic of malicious code threatening P2P systems can be divided into the active and passive propagation models and a new passive propagation model of malicious code is proposed, which differentiates peers into 4 kinds of state and fits better for actual P2P networks. From the propagation model of malicious code, it is easy to find that quickly making peers get their patched and upgraded anti-virus system is the key way of immunization and damage control. To distribute patches and immune modules efficiently, a new exponential tree plus （ET＋） and vaccine distribution algorithm based on ET＋ are also proposed. The performance analysis and test results show that the vaccine distribution algorithm based on ET＋ is robust, efficient and much more suitable for P2P networks.

关键词： data security and computer security computer virus,peer-to-peer computing propagation immune exponential tree.

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活性壳体温压战斗部对相控阵雷达天线的毁伤效应

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兵工学报 2024年第6期45卷 1725-1734页

作者：焦晓龙徐豫新吴宗娅周彤北京理工大学爆炸科学与技术国家重点实验室北京100081 北京理工大学重庆创新中心重庆401120 山西江阳化工有限公司山西太原030041

研究活性壳体与温压炸药组合战斗部的威力,以及对相控阵雷达天线靶标的毁伤效应,以期提升对其的毁伤效果,并为相关战斗部设计提供支撑。设计活性壳体、20号钢壳体2种同尺寸结构温压战斗部,进行战斗部毁伤模拟相控阵雷达天线靶标试验,测... 详细信息

研究活性壳体与温压炸药组合战斗部的威力,以及对相控阵雷达天线靶标的毁伤效应,以期提升对其的毁伤效果,并为相关战斗部设计提供支撑。设计活性壳体、20号钢壳体2种同尺寸结构温压战斗部,进行战斗部毁伤模拟相控阵雷达天线靶标试验,测试并分析火球温度、冲击波、靶标介质棒损坏比例等数据。试验结果表明:相同尺寸结构和装药量下,相对钢壳战斗部,活性壳体战斗部火球最高温度提高14.9%、500℃以上火球面积增加20%~50%,冲击波比冲量始终高于钢壳战斗部,对8 m处靶标的毁伤程度提升15.5%;温压战斗部可通过自然破片和冲击波毁伤靶标,冲击波能够造成介质棒大面积脱落,基于试验结果分析,对于54.8%以上阵面辐射单元毁伤,冲击波比冲量应达到142.5 Pa·s以上。

关键词：活性壳体温压炸药相控阵雷达天线毁伤效应

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Resource pre-allocation algorithms for low-energy task scheduling of cloud computing

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Journal of Systems Engineering and Electronics 2016年第2期27卷 457-469页

作者： xiaolong xu Lingling Cao Xinheng Wang College of Computer Nanjing University of Posts and Telecommunications Nanjing 210003 China School-of Computing University of the West of Scotland Paisley PA12BE UK

In order to lower the power consumption and improve the coefficient of resource utilization of current cloud computing systems, this paper proposes two resource pre-allocation algorithms based on the ＂shut down the redundant, turn on the demanded＂ strategy here. Firstly, a green cloud computing model is presented, abstracting the task scheduling problem to the virtual machine deployment issue with the virtualization technology. Secondly, the future workloads of system need to be predicted： a cubic exponential smoothing algorithm based on the conservative control（CESCC） strategy is proposed, combining with the current state and resource distribution of system, in order to calculate the demand of resources for the next period of task requests. Then, a multi-objective constrained optimization model of power consumption and a low-energy resource allocation algorithm based on probabilistic matching（RA-PM） are proposed. In order to reduce the power consumption further, the resource allocation algorithm based on the improved simulated annealing（RA-ISA） is designed with the improved simulated annealing algorithm. Experimental results show that the prediction and conservative control strategy make resource pre-allocation catch up with demands, and improve the efficiency of real-time response and the stability of the system. Both RA-PM and RA-ISA can activate fewer hosts, achieve better load balance among the set of high applicable hosts, maximize the utilization of resources, and greatly reduce the power consumption of cloud computing systems.

关键词： green cloud computing power consumption prediction resource allocation probabilistic matching simulated annealing

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股份回购与公司资金成本:财务风险视角

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南京审计大学学报 2024年第3期21卷 50-61页

作者：顾小龙许紫薇广东财经大学智能财会管理学院广东广州510320 广东财经大学会计学院广东广州510320

以2005—2022年沪深A股上市公司股份回购数据为样本,考察回购前后资金成本变化情况,发现股份回购后企业资金成本呈上升趋势,其中,对于财务风险大的公司,回购导致资金成本上升的情况更加明显。进一步研究也表明,财务风险大的公司,在回购... 详细信息

以2005—2022年沪深A股上市公司股份回购数据为样本,考察回购前后资金成本变化情况,发现股份回购后企业资金成本呈上升趋势,其中,对于财务风险大的公司,回购导致资金成本上升的情况更加明显。进一步研究也表明,财务风险大的公司,在回购宣告后,其长期市场反应也更差。研究从资金成本角度解释了当前中国股份回购长期价值缺失的原因,揭示出股份回购的长期价值效应受企业内部条件的作用。

关键词：股份回购权益资金成本债务资金成本过度负债融资约束破产风险长期市场反应

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