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Computers, Materials & Continua 2021年第5期67卷 1399-1412页

作者： Abdul Hannan Khan Muhammad Adnan Khan Sagheer Abbas Shahan Yamin Siddiqui Muhammad Aanwar Saeed Majed Alfayad Nouh Sabri Elmitwally School of Computer Sciences National College of Business Administration and EconomicsLahore54000Pakistan Department of Computer Science&iT Minhaj University LahoreLahore54000Pakistan Department of Computer Science Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science Virtual University of PakistanIslamabad45000Pakistan Department of information Systems College of Computer and Information SciencesJouf UniversitySkakaAljouf72341Saudi Arabia Department of Computer Science College of Computer and Information SciencesJouf UniversitySkakaAljouf72341Saudi Arabia Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo UniversityGiza12613Egypt

Artificial intelligence(Ai)is expanding its roots in medical *** acute and chronic diseases can be identified accurately at the initial level by using Ai methods to prevent the progression of health *** diseases are producing a high impact on global health and medical practitioners are suggested that the diagnosis at earlier stages is one of the foremost approaches to avert chronic kidney disease and renal *** blood pressure,diabetes mellitus,and glomerulonephritis are the root causes of kidney ***,the present study is proposed a set of multiple techniques such as simulation,modeling,and optimization of intelligent kidney disease prediction(SMOiKD)which is based on computational intelligence ***,seven parameters were used for the fuzzy logic system(FLS),and then twenty-five different attributes of the kidney dataset were used for the artificial neural network(ANN)and deep extreme machine learning(DEML).The expert system was proposed with the assistance of medical *** the quick and accurate evaluation of the proposed system,Matlab version 2019 was *** proposed SMOiKD-FLSANN-DEML expert system has shown 94.16%*** this study concluded that SMOiKD-FLS-ANN-DEML system is effective to accurately diagnose kidney disease at initial levels.

关键词： Fuzzy logic system artificial neural network deep extreme machine learning feed-backward propagation SMOiKD-FLS SMOiKD-ANN SMOiKD-DEML SMOiKD-FLS-ANN-DEML

Reliability Analysis of Heterogeneous Sensor-Cloud Systems against Targeted Attacks

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China Communications 2022年第8期19卷 181-197页

作者： Hao Peng Zhen Qian Guangquan Xu Kejie Mao Kangtian Li Dandan Zhao Department of Computer Science and Engineering Zhejiang Normal UniversityJinhua Zhejiang 321004China Key Laboratory of intelligent Education Technology and Application of Zhejiang Province Zhejiang Normal UniversityJinhua Zhejiang 321004China The Big Data School Qingdao Huanghai UniversityQingdao Shandong 266427China College of intelligence and Computing Tianjin UniversityTianjin 300072China

Based on the wide application of cloud computing and wireless sensor networks in various fields,the Sensor-Cloud System(SCS)plays an indispensable role between the physical world and the network ***,due to the close connection and interdependence between the physical resource network and computing resource network,there are security problems such as cascading failures between systems in the *** this paper,we propose a model with two interdependent networks to represent a sensor-cloud ***,based on the percolation theory,we have carried out a formulaic theoretical analysis of the whole process of cascading *** the system’s subnetwork presents a steady state where there is no further collapse,we can obtain the largest remaining connected subgroup components and the penetration ***,this result is the critical maximum that the coupled SCS can *** verify the correctness of the theoretical results,we further carried out actual simulation *** results show that a scale-free network priority attack’s percolation threshold is always less than that of ER network which is priority ***,when the scale-free network is attacked first,adding the power law exponentλcan be more intuitive and more effective to improve the network’s reliability.

关键词： sensor-cloud systems targeted attacks heterogeneous networks reliability analysis system security

Chemicohydrographic characteristics of the Yellow Sea Cold Water Mass

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Acta Oceanologica Sinica 2015年第6期34卷 5-11页

作者： XiN Ming MA Deyi WANG Baodong College of Environmental Science and Engineering Ocean University of China The First institute of Oceanography State Oceanic Administration

Based on the field data obtained during summer cruises in 2006, the overall perspective of chemical and hydrographic characteristics of the Yellow Sea Cold Water Mass （YSCWM） are discussed through the cross- YSCWM transect profiles and horizontal distributions of hydrological and chemical variables, with emphasis on the differences between the northern Yellow Sea Cold Water Mass （NYSCWM） and the southern Yellow Sea Cold Water Mass （SYSCWM）. The results show that YSCWM is characterized by low temperature （〈10℃） and dissolved oxygen （DO） concentration, high salinity （〉32.0） and nutrient concentrations. Compared to the SYSCWM, the NYSCWM possesses lower values of temperature, salinity and nutrient concentrations but higher values of DO. Also its smaller variation ranges of variables （except for temperature） demonstrate that NYSCWM is more uniform than that of SYSCWM. in addition, thermocline is more intensive in the SYSCWM than that of NYSCWM. Furthermore, DO and Chl a maxima appear at the depth of 30 m in the SYSCWM, while these phenomena are not obvious in the NYSCWM.

关键词： Yellow Sea Cold Water Mass (YSCWM) horizontal distribution vertical profile chemicohydrographic characteristics

Data and Machine Learning Fusion Architecture for Cardiovascular Disease Prediction

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Computers, Materials & Continua 2021年第11期69卷 2717-2731页

作者： Munir Ahmad Majed Alfayad Shabib Aftab Muhammad Adnan Khan Areej Fatima Bilal Shoaib Mohammad Sh.Daoud Nouh Sabri Elmitwally School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan College of Computer and information Sciences Jouf UniversitySakaka72341Saudi Arabia Department of Computer Science Virtual University of PakistanLahore54000Pakistan Riphah School of Computing&innovation Riphah International UniversityLahore CampusLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science Minhaj University LahoreLahore54000Pakistan College of Engineering Al Ain UniversityAbu Dhabi112612UAE Department of Computer Science Faculty of Computers and Artificial IntelligenceCairo University12613Egypt

Heart disease,which is also known as cardiovascular disease,includes various conditions that affect the heart and has been considered a major cause of death over the past *** and timely detection of heart disease is the single key factor for appropriate investigation,treatment,and prescription of *** technologies such as fog,cloud,and mobile computing provide substantial support for the diagnosis and prediction of fatal diseases such as diabetes,cancer,and cardiovascular *** computing provides a cost-efficient infrastructure for data processing,storage,and retrieval,with much of the extant research recommending machine learning(ML)algorithms for generating models for sample *** is considered best suited to explore hidden patterns,which is ultimately helpful for analysis and ***,this study combines cloud computing with ML,collecting datasets from different geographical areas and applying fusion techniques to maintain data accuracy and consistency for the ML *** recommended model considered three ML techniques:Artificial Neural Network,Decision Tree,and Naïve ***-time patient data were extracted using the fuzzy-based model stored in the cloud.

关键词： Machine learning fusion cardiovascular disease data fusion fuzzy system disease prediction

Binary interaction of typhoons Soulik and Cimaron in 2018—Part Ⅰ:Observational characteristics and forecast error

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Tropical Cyclone Research and Review 2021年第1期10卷 32-42页

作者： Eun-Jeong Cha Sug-gyeong Yun il-Ju Moon Dong-Hoon Kim Meso-scale Research Team Convergence Meteorological Research DepartmentNational Institute of Meteorological SciencesKorea Meteorological AdministrationSeogwipoRepublic of Korea Typhoon Research Center Jeju National UniversityJejuRepublic of Korea Artificial intelligence Convergence Research Center Inha UniversityIncheonRepublic of Korea

To understand structural changes and forecast error,a case study of binary typhoons in the western North Pacific(WNP)of 2018 was investigated using best track and reanalysis *** was generated on August 16 and Cimaron was generated on August 18,*** 19 th typhoon Soulik and 20 th typhoon Cimaron co-existed from August 18 to 24 and approached each *** was located on the western side and Cimaron was located on the eastern side of the *** were located approximately 1300 km from each other at 00 UTC August *** Soulik structure began changing around August 22 and became weak and slow,while Cimaron maintained its intensity,size,and moving *** observational evidence is likely caused by the binary interaction between two typhoons within a certain distance and environmental steering flow,such as the location of the North Pacific high and strong jet stream of the northern flank of the North Pacific *** was initially forecasted to make landfall and reach Seoul;however,its track changed from northward to northeastward from August 21 to 23 according to both official guidance and unified model(UM).Four global numerical weather prediction models forecasted different tracks of *** and JGSM forecasted a northward track whereas ECMWF and GFS showed a northeastward track for 12 UTC August 21 through 12 UTC August *** latter models were similar to the best *** track forecast error and spread of Soulik were larger than those of *** mean absolute error of the maximum wind speed of Soulik was similar to the average of total typhoons in 2018.

关键词： Typhoon Soulik Cimaron Binary typhoon interaction Structure change Forecast track intensity error

Regional chemotherapy for uveal melanoma liver metastases

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international Journal of Ophthalmology(English edition) 2023年第2期16卷 293-300页

作者： Yang-Xu Tao Hao-Wen Li Jing-Ting Luo Yang Li Wen-Bin Wei Beijing Tongren Eye Center Beijing Key Laboratory of Intraocular Tumor Diagnosis and TreatmentBeijing Ophthalmology&Visual Sciences Key LabMedical Artiﬁcial Intelligence Research and Veriﬁcation Key Laboratory of the Ministry of Industry and Information TechnologyBeijing Tongren HospitalCapital Medical UniversityBeijing 100730China

Chemotherapy remains an important approach for the treatment of liver metastases from uveal melanoma(UM).Compared with systemic chemotherapy,regional chemotherapy has similar efficacy and fewer systemic adverse *** chemotherapy for UM liver metastases includes hepatic ar ter y infusion(HAi),transarterial chemoembolization(TACE),and isolated hepatic perfusion(iHP).in this review,we aim to examine the efficacy of regional chemotherapy and compare HAi,TACE,and iHP in terms of overall survival(OS).The three approaches showed no obvious difference in OS results.

关键词： uveal melanoma liver metastasis regional chemotherapy

MPHM:Model poisoning attacks on federal learning using historical information momentum

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Security and Safety 2023年第4期2卷 6-18页

作者： Lei Shi Zhen Chen Yucheng Shi Lin Wei Yongcai Tao Mengyang He Qingxian Wang Yuan Zhou Yufei Gao School of Cyber Science and Engineering Zhengzhou UniversitySongShan LaboratoryZhengzhou 450000China College of intelligence and Computing Tianjin University300072 TianjinChina School of Computer and Artificial intelligence Zhengzhou University450000 ZhengzhouChina Zhengzhou Zhengda lnformation Technology Co. Ltd450001 ZhengzhouChina

Federated learning(FL)development has grown increasingly strong with the increased emphasis on data for individuals and *** learning allows individual participants to jointly train a global model without sharing local data,which significantly enhances data ***,federated learning is vulnerable to poisoning attacks by malicious *** federated learning does not have access to the participants’training process,i.e.,attackers can compromise the global model by uploading elaborate malicious local updates to the server under the guise of normal *** model poisoning attacks usually add small perturbations to the local model after it is trained to craft harmful local updates and the attacker finds the appropriate perturbation size to bypass robust detection methods and corrupt the global model as much as *** contrast,we propose a novel model poisoning attack based on the momentum of history information(MPHM),that is,the attacker makes new malicious updates by dynamically crafting perturbations using the historical information in the local training,which will make the new malicious updates more effective and *** attack aims to indiscriminately reduce the testing accuracy of the global model with minimal *** show that in the classical defense case,our attack can significantly corrupt the accuracy of the global model compared to other advanced poisoning attacks.

关键词： Federated learning Poisoning attacks Security Privacy

Statistical Modeling of CMiP5 Projected Changes in Extreme Wet Spells over China in the Late 21st Century

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Journal of Meteorological Research 2017年第4期31卷 678-693页

作者： Lianhua ZHU Yun Li Zhihong JiANG Key Laboratory of Meteorological Disaster Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters Nanjing University of Information Science &Technology Nanjing 210044 China School of Mathematics and Statistics Nanjing University of Information Science & Technology Nanjing 210044 China business intelligence & Data Analytics Western Power WA 6000 Australia

The observed intensity, frequency, and duration（iFD） of summer wet spells, defined here as extreme events with one or more consecutive days in which daily precipitation exceeds a given threshold（the 95th percentile）, and their future changes in RCP4.5 and RCP8.5 in the late 21st century over China, are investigated by using the wet spell model（WSM） and by extending the point process approach to extreme value analysis. Wet spell intensity is modeled by a conditional generalized Pareto distribution, frequency by a Poisson distribution, and duration by a geometric distribution, respectively. The WSM is able to realistically model summer extreme rainfall spells during 1961–2005, as verified with observations at 553 stations throughout China. To minimize the impact of systematic biases over China in the global climate models（GCMs） of the Coupled Model intercomparison Project Phase 5（CMiP5）, five best GCMs are selected based on their performance to reproduce observed wet spell iFD and average precipitation during the historical period. Furthermore, a quantile–quantile scaling correction procedure is proposed and applied to produce ensemble projections of wet spell iFD and corresponding probability distributions. The results show that in the late 21st century, most of China will experience more extreme rainfall and less low-intensity rainfall. The intensity and frequency of wet spells are projected to increase considerably, while the duration of wet spells will increase but to a much less extent. The iFD changes in RCP8.5 are in general much larger than those in RCP4.5.

关键词： wet spell model extreme value theory bias correction Coupled Model intercomparison Project Phase 5

The influence Factors of Collective intelligence Emergence in Knowledge Communities Based on Social Network Analysis

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international Journal of intelligence Science 2019年第1期9卷 23-43页

作者： Zhihong Li Ya’nan Xu Kexin Li School of business administration South China University of Technology Guangzhou China School of Journalism and Communication Shandong University Jinan China

The advent of the age of information shifts the environment we live in from off-line to on-line. The prospect of Collective intelligence (Ci) is promising. Based on this background, the aim of this paper is to discover the emergence mechanism and influence factors of Ci in knowledge communities using the method of quantitative and qualitative analysis. On the basis of the previous research work, our model theorizes that the two dimensions of social network (i.e., interactive network structure and participant’s characteristics) affect two references of effectiveness (i.e. group knowledge production and participation of group decision). And this hypothetical model is validated with simulation data from “Zhihu” community. Our model has been useful since it offers some inspirations and directions to promote the level of Ci in knowledge communities.

关键词： Collective intelligence Knowledge Community Social Network Analysis Zhihu