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Enabling Smart Cities with Cognition Based intelligent Route Decision in Vehicles Empowered with Deep Extreme Learning Machine

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Computers, Materials & Continua 2021年第1期66卷 141-156页

作者： Dildar Hussain Muhammad Adnan Khan Sagheer Abbas Rizwan Ali Naqvi Muhammad Faheem Mushtaq Abdur Rehman Afrozah Nadeem School of Computational Sciences Korea Institute for Advanced StudySeoul02455Korea Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Unmanned Vehicle Engineering Sejong UniversitySeoul05006Korea Department of information Technology Khwaja Fareed University of Engineering and Information TechnologyRahim Yar Khan64200Pakistan

The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries,including the transportation *** worldwide transport departments face many obstacles following the implementation and integration of different vehicle *** of these tasks is to ensure that vehicles are autonomous,intelligent and able to grow their repository of *** learning has recently been implemented in wireless networks,as a major artificial intelligence branch,to solve historically challenging problems through a data-driven *** this article,we discuss recent progress of applying machine learning into vehicle networks for intelligent route decision and try to focus on this emerging *** Extreme Learning Machine(DELM)framework is introduced in this article to be incorporated in vehicles so they can take human-like *** present GPS compatibility issues make it difficult for vehicles to take real-time decisions under certain *** leads to the concept of vehicle controller making *** proposed DELM based system for self-intelligent vehicle decision makes use of the cognitive memory to store route *** overcomes inadequacy of the current in-vehicle route-finding technology and its *** the relevant route-related information for the ride will be provided to the user based on its *** the DELM method,a high degree of precision in smart decision taking with a minimal error rate is *** investigation,it has been observed that proposed framework has the highest accuracy rate with 70%of training(1435 samples)and 30%of validation(612 samples).Simulation results validate the intelligent prediction of the proposed method with 98.88%,98.2%accuracy during training and validation respectively.

关键词： DELM ANN ioT feedforward route decision prediction smart city

Ai-Based Hybrid Models for Predicting Loan Risk in the Banking Sector

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Big Data Mining and Analytics 2023年第4期6卷 478-490页

作者： Vikas Kumar Shaiku Shahida Saheb Preeti Atif Ghayas Sunil Kumari Jai Kishan Chandel Saroj Kumar Pandey Santosh Kumar Humanities and Management Department Dr.B.R.Ambedkar National Institute of Technology JalandharJalandhar 144027India. Mittal School of business Lovely Professional UniversityPhagwara 144402India. Department of Commerce&business administration Kanya Maha Vidyalaya(KMV)Jalandhar 144004India School of Management Gitam(to be deemed university)Bangalore 561203India Government College for Women Indra Gandhi UniversityAteli 123021India. institute of Management Studies Kurukshetra UniversityKurukshetra 136119India Department of Computer Engineering and Applications GLA UniversityMathura 281406India Department of Management Jaipuriya Institute of ManagementJaipur 302033India

Every real-world scenario is now digitally replicated in order to reduce paperwork and human labor *** Learning(ML)models are also being used to make predictions in these *** forecasting requires knowledge of these machine learning models and their distinguishing *** datasets we use as input for each of these different types of ML models,yielding different *** choice of an ML model for a dataset is critical.A loan risk model is used to show how ML models for a dataset can be linked *** purpose of this study is to look into how we could use machine learning to quantify or forecast mortgage credit *** phrase refers to the process of evaluating massive amounts of data in order to derive useful information for making decisions in a variety of *** credit risk is considered,a method based on an examination of what caused and how mortgage credit risk affected credit defaults during the still-current economic crisis of 2021 will be *** approaches to credit risk calculation will be examined,ranging from the most basic to the most *** addition,we will conduct a case study on a sample of mortgage loans and compare the results of three different analytical approaches,logistic regression,decision tree,and gradient boost to see which one produced the most commercially useful insights.

关键词： Artificial intelligence(Ai) Machine Learning(ML) loan prediction Support Vector Machine(SVM) Random Forest(RF) accuracy

Nyström-based spectral clustering using airborne LiDAR point cloud data for individual tree segmentation

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international Journal of Digital Earth 2021年第10期14卷 1452-1476页

作者： Yong Pang Weiwei Wang Liming Du Zhongjun Zhang Xiaojun Liang Yongning Li Zuyuan Wang institute of Forest Resource information Techniques Chinese Academy of ForestryBeijingPeople’s Republic of China Key Laboratory of Forestry Remote Sensing and information System of National Forestry and Grassland administration BeijingPeople’s Republic of China College of Artificial intelligence Beijing Normal UniversityBeijingPeople’s Republic of China College of Forestry Hebei Agricultural UniversityBaodingPeople’s Republic of China Department of Land Change Science Swiss Federal Institute for ForestSnow and Landscape Research WSLBirmensdorfSwitzerland

The spectral clustering method has notable advantages in *** the high computational complexity and time consuming limit its application in large-scale and dense airborne Light Detection and Ranging(LiDAR)point cloud *** proposed the Nyström-based spectral clustering(NSC)algorithm to decrease the computational *** novel NSC method showed accurate and rapid in individual tree segmentation using point cloud *** K-nearest neighbour-based sampling(KNNS)was proposed for the Nyström approximation of voxels to improve the *** NSC algorithm showed good performance for 32 plots in China and *** overall matching rate and extraction rate of proposed algorithm reached 69%and 103%.For all trees located by Global Navigation Satellite System(GNSS)calibrated tape-measures,the tree height regression of the matching results showed an value of 0.88 and a relative root mean square error(RMSE)of 5.97%.For all trees located by GNSS calibrated total-station measures,the values were 0.89 and 4.49%.The method also showed good performance in a benchmark dataset with an improvement of 7%for the average matching *** results demonstrate that the proposed NSC algorithm provides an accurate individual tree segmentation and parameter estimation using airborne LiDAR point cloud data.

关键词： Tree segmentation airborne LiDAR spectral clustering Nyström approximation sampling method

Blockchain Use Cases Revisited:Micro-Lending Solutions for Retail Banking and Financial inclusion

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Journal of Systems Science and information 2021年第1期9卷 1-15页

作者： Christian Hugo HOFFMANN Universily of Zurich Deputy Director of the Suwiss Fin Tech Innovation LabHead of Artificial Intelligence(AD)Plaltenstrasse 148032 ZurichSwilzerland

While blockchain technology is commonly considered potentially disruptive in various regards,there is a lack of understanding where and how blockchain technology is effectively applicable and where it has remarkable practical effects~([1]).Against this background,we present and discuss a case study at length on the impact of this technology in the concrete setting of small short-term loans in retail *** propose to banks a robust and scalable blockchain technology with proof of stake and limited energy consumption used to streamline their processes,resulting in lower transaction and administration *** is made possible by smart ***,we facilitate small scale lending at high frequencies and short-term duration as well as an easier and more efficient way to connect small borrowers and lenders.

关键词： design science blockchain smart contracts asymmetric information fintech microfinance

模拟中国四级行政尺度下耕地位移对粮食生产潜力的影响

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Journal of Geographical Sciences 2023年第1期33卷 18-36页

作者：杨柏寒盛思雨柯新利代先华卢新海 College of Public administration Central China Normal UniversityWuhan 430079China College of Public administration Huazhong Agricultural UniversityWuhan 430070China College of Public administration Huazhong University of Science and TechnologyWuhan 430074China

Cropland displacement, as an important characteristic of cropland change, places more emphasis on changes in spatial location than on quantity. The effects of cropland displacement on global and regional food production are of general concern in the context of urban expansion. Few studies have explored scale-effects, however, where cropland is displaced not only within, but also outside, the administrative boundary of a certain region. This study used a spatially explicit model(LANDSCAPE) to simulate the potential cropland displacement caused by urban land expansion from 2020 to 2040 at four scales of the Chinese administration system(national, provincial, municipal, and county levels). The corresponding changes in potential cereal production were then assessed by combining cereal productivity data. The results show that 4700 km^(2) of cropland will be occupied by urban expansion by 2040, and the same amount of cropland will be supplemented by forest, grassland, wetland, and unused land. The potential loss of cropland will result in the loss of 3.838×10^(6) tons of cereal production, and the additional cropland will bring 3.546×10^(6) tons, 3.831×10^(6) tons, 3.836×10^(6) tons, and 3.528×10^(6) tons of potential cereal production in SN(national scale), SP(provincial scale), SM(municipal scale), and SC(county scale), respectively. Both SN and SC are observed to make a huge difference in cereal productivity between the lost and the supplemented cropland. We suggest that China should focus on the spatial allocation of cropland during large-scale displacement, especially at the national level.

关键词： cropland displacement potential cereal production LANDSCAPE model scale-effects food security

QpefBD:A Benchmark Dataset Applied to Machine Learning for Minute-Scale Quantitative Precipitation Estimation and Forecasting

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Journal of Meteorological Research 2022年第1期36卷 93-106页

作者： Anyuan XiONG Na LiU Yujia LiU Shulin ZHi Linlin WU Yongjian XiN Yan SHi Yunjian ZHAN National Meteorological information Center China Meteorological AdministrationBeijing 100081 Jiangxi Meteorological Observatory Nanchang 330096 Anhui Weather Modification Office Hefei 230061

Nowcasts of strong convective precipitation and radar-based quantitative precipitation estimations have always been hot yet challenging issues in meteorological ***-driven machine learning,especially deep learning,provides a new technical approach for the quantitative estimation and forecasting of precipitation.A high-quality,large-sample,and labeled training dataset is critical for the successful application of machine-learning technology to a specific *** present study develops a benchmark dataset that can be applied to machine learning for minutescale quantitative precipitation estimation and forecasting(QpefBD),containing 231,978 samples of 3185 heavy precipitation events that occurred in 6 provinces of central and eastern China from April to October *** individual sample consists of 8 products of weather radars at 6-min intervals within the time window of the corresponding event and products of 27 physical quantities at hourly intervals that describe the atmospheric dynamic and thermodynamic *** data labels,i.e.,ground precipitation intensity and areal coverage of heavy precipitation at 6-min intervals,are also *** present study describes the basic components of the dataset and data processing and provides metrics for the evaluation of model performance on precipitation estimation and *** on these evaluation metrics,some simple and commonly used methods are applied to evaluate precipitation estimates and *** results can serve as the benchmark reference for the performance evaluation of machine learning models using this *** paper also gives some suggestions and scenarios of the QpefBD *** believe that the application of this benchmark dataset will promote interdisciplinary collaboration between meteorological sciences and artificial intelligence sciences,providing a new way for the identification and forecast of heavy precipitation.

关键词： machine learning benchmark dataset quantitative precipitation estimation precipitation forecast

The Effects of Breaststroke Kick Electromyography Muscle Activity

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Psychology Research 2021年第8期11卷 363-368页

作者： Takahisa ide M.A. William F.Johnson Sadafumi Takise Jan Konarzewski Noriko inada Hiromasa Fujimori Takeharu Fujimori Emi Moronuki Ken A.Barcinas Kohei Kawamoto Kazuki Watanabe Asahi Nagahata iryna Glavnyk Daniil Antipov Mark Nikolaev Bogdan Plavin Osaka University of Health and Sport Sciences OsakaJapanPhoenix Swim ClubParadise ValleyUSAGrand Canyon UniversityPhoenixUSA TexasA&M University Corpus Christi Corpus ChristiUSA Osaka University of Health and Sport Sciences OsakaJapan University of Edinburgh in Computer Science B.A.in Informatics and Social ComputingUniversity of MichiganSwimming SciencPhoenix Swim ClubParadise ValleyUSA. Department of Education Waseda UniversitySwimming SciencePhoenix Swim ClubParadise ValleyUSA. Faculty of Sport Science of Nippon Sports Science University Swimming SciencePhoenix Swim ClubParadise ValleyUSA. School of Health and Physical Education Tsukuba UniversitySwimming SciencePhoenix Swim ClubParadise ValleyUSA. Faculty of Management information of Yamanashi Gakuin University JapanSwimming SciencePhoenix Swim ClubParadise ValleyUSA. Department of Economics Faculty of EconomicsChuo UniversitySwimming SciencesPhoenix Swim ClubParadise ValleyUSA. Meiji University School of CommercePhoenix Swim ClubParadise ValleyUSA. business administration with an emphasis i busiiness intelligence Grand CanyonUniversityPhoenixUSA. Bussiness Management of Marketing and Enterpreneurship Grand Canyon UniversityPhoenixUSA. Arts in Goverment with an emphasis in Legal Studies Grand Canyon UniversityPhoenixUSA.Grand Canyon UniversityPhoenixUSA. Grand Canyon University PhoenixUSAWashingtonD.C.TridentBaarSwitzerland. Grand Canyon University PhoenixUSAScience in Information TechnologyValparaiso UniversityValparaisoUSA.

This paper evaluates the efficiency of using a downward breaststroke kick in a sample of eight elite *** a downward breaststroke kick increases the one stroke velocity and max speed but also increases production of lactate *** the downward breaststroke kick we find the 100-meter and 100-yard breaststroke times decrease from 1:05.10s to 1:01.97s and find the downward breaststroke kick increases muscle activity of the quadriceps,biceps,and *** increases in performance were observed from measuring the world class swimmers are highly correlated to duration of the kick aerodynamic buoyant force in breaststroke.

关键词： swimming breaststroke electromyography downward kick Olympians psychology

3D Kronecker Convolutional Feature Pyramid for Brain Tumor Semantic Segmentation in MR imaging

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Computers, Materials & Continua 2023年第9期76卷 2861-2877页

作者： Kainat Nazir Tahir Mustafa Madni Uzair iqbal Janjua Umer Javed Muhammad Attique Khan Usman Tariq Jae-Hyuk Cha Medical imaging and Diagnostics Lab NCAIDepartment of Computer ScienceCOMSATS University IslamabadIslamabad44000Pakistan Department of Electrical and Computer Engineering COMSATS University IslamabadWah CampusWahPakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Management information Systems College of Business AdministrationPrince Sattam Bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Computer Science Hanyang UniversitySeoul04763Korea

Brain tumor significantly impacts the quality of life and changes everything for a patient and their loved *** a brain tumor usually begins with magnetic resonance imaging(MRi).The manual brain tumor diagnosis from the MRO images always requires an expert ***,this process is time-consuming and ***,a computerized technique is required for brain tumor detection in MRi *** the MRi,a novel mechanism of the three-dimensional(3D)Kronecker convolution feature pyramid(KCFP)is used to segment brain tumors,resolving the pixel loss and weak processing of multi-scale lesions.A single dilation rate was replaced with the 3D Kronecker convolution,while local feature learning was performed using the 3D Feature Selection(3DFSC).A 3D KCFP was added at the end of 3DFSC to resolve weak processing of multi-scale lesions,yielding efficient segmentation of brain tumors of different sizes.A 3D connected component analysis with a global threshold was used as a post-processing *** standard Multimodal Brain Tumor Segmentation 2020 dataset was used for model *** 3D KCFP model performed exceptionally well compared to other benchmark schemes with a dice similarity coefficient of 0.90,0.80,and 0.84 for the whole tumor,enhancing tumor,and tumor core,***,the proposed model was efficient in brain tumor segmentation,which may facilitate medical practitioners for an appropriate diagnosis for future treatment planning.

关键词： Brain tumor segmentation connect component analysis deep learning kronecker convolution magnetic resonance imaging

international exchange and collaboration in science

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National Science Review 2019年第6期6卷 1063-1063页

作者： Mu-ming Poo CAS Center for Excellence in Brain Science and intelligence Technology NSR

Scientific exchange and collaboration between the two largest economies in the world are now facing serious challenges, due to isolationist policies of the Trump administration. The USA has been the leading country in attracting international talents and in promoting scientific exchange and collaboration. The sudden change in the climate appears to be triggered by the

关键词： international exchange and collaboration in science