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Heavy metals prediction in coastal marine sediments using hybridized machine learning models with metaheuristic optimization algorithm

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Chemosphere 2024年 352卷 141329页

作者： Yaseen, Zaher Mundher Melini Wan Mohtar, Wan Hanna Homod, Raad Z. Alawi, Omer A. Abba, Sani I. Oudah, Atheer Y. Togun, Hussein Goliatt, Leonardo Ul Hassan Kazmi, Syed Shabi Tao, Hai Civil and Environmental Engineering Department King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Research Center for Membranes and Water Security King Fahd University of Petroleum & Minerals (KFUPM) Dhahran Saudi Arabia Department of Civil Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia UKM Selangor Bangi 43600 Malaysia Environmental Management Centre Institute of Climate Change Universiti Kebangsaan Malaysia Selangor UKM Bangi 43600 Malaysia Department of Oil and Gas Engineering Basrah University for Oil and Gas Basra Iraq Department of Thermofluids School of Mechanical Engineering Universiti Teknologi Malaysia UTM Skudai Johor Bahru 81310 Malaysia Department of Computer Sciences College of Education for Pure Science University of Thi-Qar Nasiriyah 64001 Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Nasiriyah 64001 Iraq Department of Mechanical Engineering College of Engineering University of Baghdad Baghdad Iraq Computational and Applied Mechanics Department Federal University of Juiz de Fora 36036-900 Brazil Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention and Guangdong Provincial Key Laboratory of Marine Biotechnology Shantou University Shantou 515063 China School of Computer and Information Qiannan Normal University for Nationalities Guizhou Duyun 558000 China Institute of Big Data Application and Artificial Intelligence Qiannan Normal University for Nationalities Guizhou Duyun 558000 China Faculty of Data Science and Information Technology INTI International University 71800 Malaysia

This study proposes different standalone models viz: Elman neural network (ENN), Boosted Tree algorithm (BTA), and f relevance vector machine (RVM) for modeling arsenic (As (mg/kg)) and zinc (Zn (mg/kg)) in marine sediments owing to anthropogenic activities. A heuristic algorithm based on the potential of RVM and a flower pollination algorithm (RVM-FPA) was developed to improve the prediction performance. Several evaluation indicators and graphical methods coupled with visualized cumulative probability function (CDF) were used to evaluate the accuracy of the models. Akaike (AIC) and Schwarz (SCI) information criteria based on Dickey-Fuller (ADF) and Philip Perron (PP) tests were introduced to check the reliability and stationarity of the data. The prediction performance in the verification phase indicated that RVM-M2 (PBAIS = -o.0465, MAE = 0.0335) and ENN-M2 (PBAIS = 0.0043, MAE = 0.0322) emerged as the best model for As (mg/kg) and Zn (mg/kg), respectively. In contrast with the standalone approaches, the simulated hybrid RVM-FPA proved merit and the most reliable, with a 5 % and 18 % predictive increase for As (mg/kg) and Zn (mg/kg), respectively. The study's findings validated the potential for estimating complex HMs through intelligent data-driven models and heuristic optimization. The study also generated valuable insights that can inform the decision-makers and stockholders for environmental management strategies. © 2024 Elsevier Ltd

关键词： Artificial intelligence Heavy metals Sensitivity analysis Soil contamination

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Difference in Differences in Marketing Performance Measurement

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Procedia Computer Science 2019年 162卷 275-280页

作者： Wei Deng Nan Xu Haotian Li Fangyao Liu Yong Shi University of Nebraska at Omaha Omaha NE 68182 Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China

Marketing performance measurement is important in retail companies, it is critical for the budget planning and adjustment of marketing strategies and tactics over time. Compared to digital online marketing, such as social media advertisers where tagging techniques [1] can be applied to track the lifecycle of the consumption and the customer’s behaviours, traditional TV and radio advertising will be harder to evaluate at the individual level. Instead, common approach in this scenario is to study the relationship between ads spend and sales. This paper presents a casual inference methodology – “Difference in Differences”(DID) on the application of TV marketing measurement. Instead of building direct relationship between ads and sales, we attempt to create an experimental research design and study the differential effect on a ‘treatment group’ versus a ‘control group’. In order to study the performance of advertising in a city, the treatment group is sales performance during and after TV advertisings and the control group is the statistical model that mimics the sales of the same city without ads influence. It is proved that the model can significantly predict the sales of city in nature by considering its past sales, the neighbourhood districts and weather conditions. And a case study in industrial data shows that DID methodology can effectively evaluate the TV advertising results on regions.

关键词： Advertising Measurement Difference in Differences Random Forest Lasso Regression

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Compressed Gradient Tracking for Decentralized Optimization Over General Directed Networks

arXiv

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arXiv 2021年

作者： Song, Zhuoqing Shi, Lei Pu, Shi Yan, Ming Shanghai Center for Mathematical Sciences Fudan University Shanghai China School of Mathematical Sciences Shanghai Key Laboratory for Contemporary Applied Mathematics Fudan University Shanghai China School of Data Science Shenzhen Research Institute of Big Data The Chinese University of Hong Kong Shenzhen China Department of Computational Mathematics Science and Engineering Department of Mathematics Michigan State University East LansingMI48864 United States

In this paper, we propose two communication-efficient decentralized optimization algorithms over a general directed multi-agent network. The first algorithm, termed Compressed Push-Pull (CPP), combines the gradient tracking Push-Pull method with communication compression. We show that CPP is applicable to a general class of unbiased compression operators and achieves linear convergence rate for strongly convex and smooth objective functions. The second algorithm is a broadcast-like version of CPP (B-CPP), and it also achieves linear convergence rate under the same conditions on the objective functions. B-CPP can be applied in an asynchronous broadcast setting and further reduce communication costs compared to CPP. Numerical experiments complement the theoretical analysis and confirm the effectiveness of the proposed methods. Copyright © 2021, The Authors. All rights reserved.

关键词： Directed graphs

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Erratum to: Novel Test Scenario Generation Technology for Performance Evaluation of Automated Vehicle

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International Journal of Automotive Technology 2023年第6期24卷 1691-1691页

作者： Li, Shuang Li, Wei Li, Penghui Ma, Ping Yang, Ming Control and Simulation Center Harbin Institute of Technology Harbin China Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport the School of Traffic and Transportation Beijing Jiaotong University Beijing China State Key Laboratory of Vehicle NVH and Safety Technology China Automotive Engineering Research Institute Co. Ltd. Chongqing China

This is the Editorial Board of the International Journal of Automotive Technology. In 11th Feb, 2022 we accepted a paper entitled “Novel Test Scenario Generation Technology for Performance Evaluation of Automated Vehicle”. According to the request from the authors of this article, we make a correction announcement of the grant number. Please refer to Table 1 for details.

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Fault Diagnosis and Fault-Tolerant Attitude Control of Spacecraft Based on Combined Observer

Fault Diagnosis and Fault-Tolerant Attitude Control of Space...

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第40届中国控制会议

作者： Yuandong Li Yizhong Fang Menghan Shao Xuning Chen Xiaodong Shao Qinglei Hu Jianying Zheng School of Automation Science and Electrical Engineering Beihang University The State Key Laboratory of Experiment Physics & Computational Mathematic Beijing Institute of Space Long March Vehicle Beijing Aerospace Automatic Control Institute China Academy of Launch Vehicle Technology School of Aeronautic Science and Engineering Beihang University Beijing Advanced Innovation Center for Big-Data Based Precision Medicine Beihang University

Reaction wheels as the main actuators for attitude control of spacecraft are very prone to malfunction,which may significantly degrade the performance of the spacecraft attitude control *** this paper a novel active fault-tolerant control scheme is proposed to react the reaction wheel faults actively.A combined observer is first designed to detect the reaction wheel faults,by combining a traditional adaptive Luenberger observer and a newly designed neural network（NN） *** inherits the advantages of the low computational cost of the Luenberger observer and the high performance of the NN ***,a fault isolation scheme is given to locate ***,an adaptive fault-tolerant controller is designed to achieve graceful performance degradation under reaction wheel faults,based on the diagnosis results of the combined observer and the judgment results of the fault isolation ***,simulation results show that the proposed scheme is able to achieve precise fault diagnosis and fault-tolerant control of spacecraft in the presence of external interference and limited computation.

关键词： neural network observer fault-tolerant control fault diagnosis spacecraft attitude control

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Energy calibration of HPGe detector using the high-energy characteristic γ rays in 13C formed in 6Li + 12C reaction

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Nuclear Science and Techniques 2020年第5期31卷 57-63页

作者： Jia-Tai Li Xue-Dou Su Gao-Long Zhang Guang-Xin Zhang Shi-Peng Hu Jing-Bin Lu Yi-Feng Lv Hui-Bin Sun Huan-Qiao Zhang D.Testov P.R.John J.J.Valiente-Dobon A.Goasduff M.Siciliano F.Galtarossa F.Recchia D.Mengoni D.Bazzacco School of Physics Beihang UniversityBeijing 100191China Shenyuan Honors College Beihang UniversityBeijing 100191China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine and EngineeringBeihang University and Key Laboratory of Big Data-Based Precision Medicine(Beihang University)Ministry of Industry and Information TechnologyBeihang UniversityBeijing 100191China Dipartimento di Fisica Astronomia dell’Universit'a di PadovaPaduaItaly Istituto Nazionale di Fisica Nucleare Sezione di PadovaPaduaItaly College of Physics Science and Technology Shenzhen UniversityShenzhen 518060China College of Physics Jilin UniversityChangChun 130012China China Institute of Atomic Energy Beijing 102413China Laboratori Nazionali di Legnaro INFNLegnaroPaduaItaly Irfu/CEA Universit de Paris-SaclayGif-sur-YvetteFrance

An 6 Li+89Y experiment was conducted at the Laboratori Nazinali di Legnaro,INFN,*** 550μg/cm^2 thick^89Y target was backed on a 340μg/cm^2 thick 12C *** severalγrays in the experiment with energies higher than 3000 keV can most likely be ascribed to the transitions in the 13C nuclei,which can be formed through various interactions between the 6 Li beam and the 12C *** high-energy properties ofγrays in 13C are employed for energy calibrating HPGe detectors,especially for the>3000 keV region,which is impossible to reach by common standard sources(152Eu,133Ba,etc.).Furthermore,γ-γand particle-γcoincidence measurements were performed to investigate the formation of 13C.

关键词： Energy calibration Coincidence measurement Weakly bound nuclei Reaction mechanism

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Research on polygraph technology based on ballistocardiogram signal

Research on polygraph technology based on ballistocardiogram...

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IEEE Information Technology, Networking, Electronic and Automation Control Conference

作者： Xiaolong Li Chaoyong Deng Qiwei Wu Ruirui Cui Jintian Tang Yandong Zhang College of Big Data and Information Engineering Guizhou University Guiyang China School of Physics and Engineering Zhengzhou University Zhengzhou China Ministry of Education Key Laboratory of Particle & Radiation Imaging (Tsinghua University) Beijing China

ISBN: (数字)9781728143903

ISBN: (纸本)9781728143910

Polygraph technology has always been concerned by the society. At present, there are many technologies used in the field of lie detection research. By summarizing the characteristics of the current technology, this paper proposes a multi-channel concealed polygraph technology based on ballistocardiogram (BCG), which can make up for the shortcomings of the existing technology. In this paper, the BCG signal, image signal, speech signal and galvanic skin response (GSR) signal are used to preprocess and extract the features. Using the extracted features to train the classification model, we can get an overall accuracy of 78%, and the area under the curve (AUC) score is 0.84. This experiment proves the effectiveness and advantages of BCG signal for lie detection, and also provides an effective method for the study of concealed polygraph technology.

关键词： Feature extraction Low-pass filters Band-pass filters Sensors Cutoff frequency Physiology Skin

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Improving Object Detection of Remotely Sensed Multispectral Imagery Via Pan-sharpening 2020

Improving Object Detection of Remotely Sensed Multispectral ...

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Proceedings of the 2020 9th International Conference on Computing and Pattern Recognition

作者： Feng Chen Shenlong Lou Yuejun Song College of Computer and Information Engineering Xiamen University of Technology Big Data Institute of Digital Natural Disaster Monitoring in Fujian Xiamen University of Technology Xiamen China and Fujian Key Laboratory of Sensing and Computing for Smart Cities School of Informatics Xiamen University Xiamen China UNISOC Pudong New Area Shanghai China Jiangxi Key Laboratory of Soil Erosion and Prevention Jiangxi Institute of Soil and Water Conservation Nanchang Jiangxi Province China

ISBN: (纸本)9781450387835

Pan-sharpening is used to fuse multispectral images with low spatial resolution and a panchromatic (Pan) image with high spatial resolution to generate synthesized images featured with high spatial and multispectral properties. The pan-sharpened images are assumed valuable for further application. However, there have been a few investigations on the effectiveness of the pan-sharpened products in practice (i.e. object detection), compared with the fact many algorithms for pan-sharpening have been developed. In this paper, improvements contributed by pan-sharpening process for the object detection in multispectral imagery were investigated. Original multispectral images along with the corresponding Pan images acquired by Gaojing-1 (SuperView-1, as the first sub-meter high-resolution commercial remote sensing satellite independently developed in China) satellite were used. Seven algorithms widely used in pan-sharpening were applied separately and compared, while the object detection experiments were done by implementing Faster RCNN. The preliminary findings show: (1) the pan-sharpened images present obviously positive contribution to object detection with Faster RCNN, compared to the original multispectral images; (2) detection results of the pan-sharpened images vary with the algorithms used in pan-sharpening process. Furthermore, this investigation suggests none of the pan-sharpening algorithms showed absolute advantages in image fusion to achieve better object detection consequently.

关键词： SuperView-1 multispectral imagery spatial resolution Faster RCNN Pan-sharpening

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Generating High-quality Movie Tags from Social Reviews: A Learning-driven Approach

Generating High-quality Movie Tags from Social Reviews: A Le...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Zhenxiao Luo Guopin Tang Chen Wang Yipeng Zhou Xi Zheng Jessie Hui Wang Gang Liu Di Wu School of Computer Science and Engineering Sun Yat-Sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China Faculty of Science and Engineering Macquarie University Sydney Australia Institute for Network Sciences and Cyberspace Beijing National Research Center for Information Science and Technology Tsinghua University Beijing China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

ISBN: (纸本)9781665417631

As a kind of keywords to describe video contents, tags are extremely beneficial for viewers to locate videos when they search the site. Additionally, tags also help video platform operators to better organize and recommend videos to platform users. Previous approaches are mainly based on manually tagging or tag propagation via video content analysis, which is time-consuming and resource-consuming. Especially, given the high volume of fresh movies generated per year, it is difficult to accurately tag all the movies manually. Moreover, video content analysis is also not easy considering typical features (e.g., long duration, complicated scenarios) of commercial movies. In this paper, we propose an automatic tagging algorithm called TagRec that exploits crowdsourced user reviews to generate accurate movie tags. We observe that user reviews contain rich information about movies (e.g., quality, actors) which can be learned to generate high-quality movie tags. Inspired by the above observation, we choose to transform the movie video tagging problem into a tag recommendation problem, in which tags are recommended to different movies by extracting knowledge from crowdsourced movie reviews. We take latent topics, tag co-occurrence probability and tag semantics into account, and formulate the problem as a recommendation optimization problem. We evaluate the performance of our pro-posed TagRec algorithm with a large-scale real-world dataset. Extensive experiments demonstrate that TagRec achieves 7.1 % and 9.6% improvement compared with other state-of-the-art methods in terms of Hit Ratio and Normalized Discounted Cumulative Gain respectively.

关键词： Social computing Filtering Semantics Transforms Tagging Motion pictures Optimization

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Towards 6G wireless communication networks:vision, enabling technologies, and new paradigm shifts

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Science China(Information Sciences) 2021年第1期64卷 5-78页

作者： Xiaohu YOU Cheng-Xiang WANG Jie HUANG Xiqi GAO Zaichen ZHANG Mao WANG Yongming HUANG Chuan ZHANG Yanxiang JIANG Jiaheng WANG Min ZHU Bin SHENG Dongming WANG Zhiwen PAN Pengcheng ZHU Yang YANG Zening LIU Ping ZHANG Xiaofeng TAO Shaoqian LI Zhi CHEN Xinying MA Chih-Lin I Shuangfeng HAN Ke LI Chengkang PAN Zhimin ZHENG Lajos HANZO Xuemin (Sherman) SHEN Yingjie Jay GUO Zhiguo DING Harald HAAS Wen TONG Peiying ZHU Ganghua YANG Jun WANG Erik G.LARSSON Hien Quoc NGO Wei HONG Haiming WANG Debin HOU Jixin CHEN Zhe CHEN Zhangcheng HAO Geoffrey Ye LI Rahim TAFAZOLLI Yue GAO H.Vincent POOR Gerhard P.FETTWEIS Ying-Chang LIANG National Mobile Communications Research Laboratory School of Information Science and EngineeringSoutheast University Purple Mountain Laboratories Shanghai Institute of Fog Computing Technology (SHIFT) ShanghaiTech University Research Center for Network Communication Peng Cheng Laboratory State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications National Engineering Laboratory for Mobile Network Technologies Beijing University of Posts and Telecommunications National Key Laboratory of Science and Technology on Communications University of Electronic Science and Technology of China (UESTC) China Mobile Research Institute School of Electronics and Computer Science University of Southampton Department of Electrical and Computer Engineering University of Waterloo Global Big Data Technologies Centre (GBDTC) University of Technology Sydney School of Electrical and Electronic Engineering The University of Manchester LiFi Research and Development Centre Institute for Digital CommunicationsSchool of EngineeringThe University of Edinburgh Huawei Technologies Canada Co. Ltd. Huawei Technologies Department of Electrical Engineering (ISY) Link?ping University Institute of Electronics Communications & Information Technology (ECIT)Queen's University Belfast State Key Laboratory of Millimeter Waves School of Information Science and EngineeringSoutheast University School of Electrical and Computer Engineering Georgia Institute of Technology 5G Innovation Centre University of Surrey Princeton University Vodafone Chair Mobile Communications Systems Technische Universit?t Dresden Center for Intelligent Networking and Communications (CINC) University of Electronic Science and Technology of China (UESTC)

The fifth generation(5G) wireless communication networks are being deployed worldwide from 2020 and more capabilities are in the process of being standardized, such as mass connectivity, ultra-reliability,and guaranteed low latency. However, 5G will not meet all requirements of the future in 2030 and beyond, and sixth generation(6G) wireless communication networks are expected to provide global coverage, enhanced spectral/energy/cost efficiency, better intelligence level and security, etc. To meet these requirements, 6G networks will rely on new enabling technologies, i.e., air interface and transmission technologies and novel network architecture, such as waveform design, multiple access, channel coding schemes, multi-antenna technologies, network slicing, cell-free architecture, and cloud/fog/edge computing. Our vision on 6G is that it will have four new paradigm shifts. First, to satisfy the requirement of global coverage, 6G will not be limited to terrestrial communication networks, which will need to be complemented with non-terrestrial networks such as satellite and unmanned aerial vehicle(UAV) communication networks, thus achieving a space-airground-sea integrated communication network. Second, all spectra will be fully explored to further increase data rates and connection density, including the sub-6GHz, millimeter wave(mmWave), terahertz(THz),and optical frequency bands. Third, facing the big datasets generated by the use of extremely heterogeneous networks, diverse communication scenarios, large numbers of antennas, wide bandwidths, and new service requirements, 6G networks will enable a new range of smart applications with the aid of artificial intelligence(AI) and big data technologies. Fourth, network security will have to be strengthened when developing 6G networks. This article provides a comprehensive survey of recent advances and future trends in these four aspects. Clearly, 6G with additional technical requirements beyond those of 5G will enable f

关键词： 6G vision network architecture air interface and transmission technologies space-air-ground-sea integrated network all spectra artificial intelligence network security

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