检索结果-南通市图书馆

Geo-Spatial Information Science 2023年第3期26卷 540-557页

作者： ali Almagbile Khaled Hazaymeh Department of Geography Applied Geoinformatics LaboratoryYarmouk UniversityIrbidJordan

The massive lockdown of human socioeconomic activities and vehicle movements due to the COVID-19 pandemic in 2020 has resulted in an unprecedented reduction in pollutant gases such as Nitrogen Dioxide(NO_(2))and Carbon Monoxide(CO)as well as Land Surface Temperature(LST)in Amman as well as all countries around the *** this study,the spatial and temporal variability/stability of NO_(2),CO,and LST throughout the lockdown period over Amman city have been *** NO_(2) and CO column density values were acquired from Sentinel-5p while the LST data were obtained from MODIS satellite during the lockdown period from 20 March to 24 April in 2019,2020,and *** statistical analysis showed an overall reduction in NO_(2) in 2020 by around 27% and 48% compared to 2019 and 2021,***,an increase of 7% in 2021 compared to 2019 was observed because almost all anthropogenic activities were allowed during the *** temporal persistence showed almost constant NO2 values in 2020 over the study area throughout the lockdown *** addition,a slight decrease in CO(around 1%)was recorded in 2020 and 2021 compared to the same period in *** on human activities resulted in an evident drop in LST in 2020 by around 13%and 18% less than the 5-year average and 2021 *** study concludes that due to the restrictions imposed on industrial activities and automobile movements in Amman city,an unprecedented reduction in NO_(2),CO,and LST was recorded.

关键词： Air quality COVID-19 lockdown spatiotemporal analysis NO_(2) CO Land Surface Temperature(LST) Sentinel-5p and MODIS satellites

Integration of maximum crop response with machine learning regression model to timely estimate crop yield

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Geo-Spatial Information Science 2021年第3期24卷 474-483页

作者： Qiming Zhou ali Ismaeel Department of Geography Hong Kong Baptist UniversityHong KongChina

Timely and reliable estimation of regional crop yield is a vital component of food security assessment, especially in developing regions. The traditional crop forecasting methods need ample time and labor to collect and process field data to release official yield reports. Satellite remote sensing data is considered a cost-effective and accurate way of predicting crop yield at pixel-level. In this study, maximum Enhanced Vegetation Index (EVI) during the crop-growing season was integrated with Machine Learning Regression (MLR) models to estimate wheat and rice yields in Pakistan’s Punjab province. Five MLR models were compared using a fivefold cross-validation method for their predictive accuracy. The study results revealed that the regression model based on the Gaussian process outperformed over other models. The best performing model attained coefficient of determination (R^(2)), Root Mean Square Error (RMSE, t/ ha), and Mean Absolute Error (MAE, t/ha) of 0.75, 0.281, and 0.236 for wheat;0.68, 0.112, and 0.091 for rice, respectively. The proposed method made it feasible to predict wheat and rice 6- 8 weeks before the harvest. The early prediction of crop yield and its spatial distribution in the region can help formulate efficient agricultural policies for sustainable social, environmental, and economic progress.

关键词： Machine learning remote sensing crop yield timely forecast

Cache in fog computing design,concepts,contributions,and security issues in machine learning prospective

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Digital Communications and Networks 2023年第5期9卷 1033-1052页

作者： Muhammad ali Naeem Yousaf Bin Zikria Rashid ali Usman Tariq Yahui Meng ali Kashif Bashir School of Science Guangdong University of Petrochemical TechnologyMaoming525000China Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Republic of Korea Department of Information and Communication Technologies Universitat Pompeu FabraBarcelonaSpain College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computing and Mathematics Manchester Metropolitan UniversityManchesterUnited Kingdom Woxsen School of Business Woxsen UniversityHyderabadIndia Department of Computer Science and Mathematics Lebanese American UniversityBeirutLebanon

The massive growth of diversified smart devices and continuous data generation poses a challenge to communication *** deal with this problem,communication networks consider fog computing as one of promising technologies that can improve overall communication *** brings on-demand services proximate to the end devices and delivers the requested data in a short *** computing faces several issues such as latency,bandwidth,and link utilization due to limited resources and the high processing demands of end *** this end,fog caching plays an imperative role in addressing data dissemination *** study provides a comprehensive discussion of fog computing,Internet of Things(IoTs)and the critical issues related to data security and dissemination in fog ***,we determine the fog-based caching schemes and contribute to deal with the existing issues of fog ***,this paper presents a number of caching schemes with their contributions,benefits,and challenges to overcome the problems and limitations of fog *** also identify machine learning-based approaches for cache security and management in fog computing,as well as several prospective future research directions in caching,fog computing,and machine learning.

关键词： Internet of things Cloud computing Fog computing Caching Latency

Impact of nanoparticle shape on thermohydraulic performance of a nanofluid in an enhanced microchannel heat sink for utilization in cooling of electronic components

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Chemical Engineering 2021年第12期34卷 36-47页

作者： Mehdi Bahiraei ali Monavari Institute of Research and Development Duy Tan UniversityDa Nang 550000Vietnam Department of Mechanical Engineering Razi UniversityKermanshahIran

In this article,the thermal–hydraulic efficacy of a boehmite nanofluid with various particle shapes is evaluated inside a microchannel heat *** study is done for particle shapes of platelet,cylinder,blade,brick,and oblate spheroid at Reynolds numbers(Re)of 300,800,1300,and *** particle volume fraction is assumed invariant for all of the nanoparticle *** heat transfer coefficient(h),flow irregularities,pressure loss,and pumping power heighten by the elevation of the Re for all of the nanoparticle ***,the nanofluid having the platelet-shaped nanoparticles leads to the greatest h,and the nanofluid having the oblate spheroid particles has the lowest h and smallest pressure *** contrast,the nanofluid having the platelet-shaped nanoparticles leads to the highest pressure *** mean temperature of the bottom surface,thermal resistance,and temperature distribution uniformity decrease by the rise in the Reynolds number for all of the particle ***,the best distribution of the temperature and the lowest thermal resistance are observed for the suspension containing the platelet ***,the thermal resistance of the nanofluid with the platelet particles shows a 9.5%decrement compared to that with the oblate spheroid particles at Re=*** all the nanoparticle shapes,the figure of merit(FoM)uplifts by elevating the Re,while the nanofluids containing the brickand oblate spheroid-shaped nanoparticles demonstrate the highest FoM values.

关键词： Nanofluid Thermohydraulic performance Nanoparticle shape Microchannel heat sink Boehmite nanoparticles

Low Impedance Fault Identification and Classification Based on Boltzmann Machine Learning for HVDC Transmission Systems

在线全文

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2022年第2期10卷 440-449页

作者： Raheel Muzzammel ali Raza the Department of Electrical Engineering University of LahoreLahore 54000Pakistan

Identification and classification of DC faults are considered as fundamentals of DC grid protection.A sudden rise of DC fault current must be identified and classified to immediately operate the corresponding interrupting *** this paper,the Boltzmann machine learning(BML)approach is proposed for identification and classification of DC faults using travelling waves generated at fault point in voltage source converter based high-voltage direct current(VSC-HVDC)transmission *** unsupervised way of feature extraction is performed on the frequency spectrum of the travelling *** class logistic regression(BCLR)classifies the HVDC transmission system into faulty and healthy *** proposed technique reduces the time for fault identification and classification because of reduced tagged data with few ***,the faults near or at converter stations are readily identified and *** performance of the proposed technique is assessed via simulations developed in MATLAB/Simulink and tested for pre-fault and post-fault data both at VSC1 and VSC2,***,the proposed technique is supported by analyzing the root mean square error to show practicality and realization with reduced computations.

关键词： Binary class logistic regression(BCLR) Boltzmann machine learning(BML) DC grid protection fault identification and classification voltage source converter based high-voltage direct current(VSC-HVDC)transmission system

Identification of structural parameters and boundary conditions using a minimum number of measurement points

在线全文

学校读者我要写书评

暂无评论

Frontiers of Structural and Civil Engineering 2020年第6期14卷 1331-1348页

作者： ali KARIMPOUR Salatn RAHMATALLA Department of Civil and Environmental Engineering and Iowa Technology Institute The University of IowaIowa CityIA 52242USA

This article proposes a novel methodology that uses mathematical and numerical models of a structure to build a data set and determine crucial nodes that possess the highest *** surfaces between the structural parameters and structural output features,represented by the natural frequencies of the structure and local transmissibility,are built using the numerical data set.A description of a possible experimental application is provided,where sensors are mounted at crucial nodes,and the natural frequencies and local transmissibility at each natural frequency are determined from the power spectral density and the power spectral density ratios of the sensor responses,*** inverse iterative process is then applied to identify the structural parameters by matching the experimental features with the available parameters in the myriad numerical data *** examples are presented to demonstrate the feasibility and efficacy of the proposed *** results reveal that the method was able to accurately identify the boundary coefficients and physical parameters of the Euler-Bemoulli beam as well as a highway bridge model with elastic foundations using only two measurement *** is expected that the proposed method will have practical applications in the identification and analysis of restored structural systems with unknown parameters and boundary coefficients.

关键词： structural model validation eigenvalue problem response surface inverse problems

Airship aerodynamic model estimation using unscented Kalman filter

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Systems Engineering and Electronics 2020年第6期31卷 1318-1329页

作者： WASIM Muhammad ali Ahsan Department of Electrical Engineering University of Engineering and TechnologyTaxila 47080Pakistan

An airship model is made-up of aerostatic,aerodynamic,dynamic,and propulsive forces and *** others,the computation of aerodynamic forces and torques is ***,wind tunnel experimentation and potential flow theory are used for their ***,the limitations of these methods pose difficulties in their accurate *** this work,an online estimation scheme based on unscented Kalman filter(UKF)is proposed for their *** proposed method introduces six auxiliary states for the complete aerodynamic *** uses an extended model and provides an estimate of a complete state vector along with auxiliary *** proposed method uses the minimum auxiliary state variables for the approximation of the complete aerodynamic model that makes it computationally less *** estimation performance is evaluated by developing a nonlinear simulation environment for University of Engineering and Technology,Taxila(UETT)*** performance is vali􀅫dated by performing the error analysis based on estimation error and 2-σ uncertainty *** the same problem,the extended Kalman filter(EKF)is also implemented and its results are compared with *** simulation results show that UKF successfully estimates the forces and torques due to the aerodynamic model with small estimation error and the comparative analysis with EKF shows that UKF improves the estimation re􀅫sults and also it is more suitable for the under-consideration problem.

关键词： airship unscented Kalman filter(UKF) extend Kalman filter(EKF) state estimation aerodynamic model estimation

Sensing the heavy water concentration in an H_(2)O-D_(2)O mixture by solid-solid phononic crystals

在线全文

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第4期33卷 493-498页

作者： Mohammadreza Rahimi ali Bahrami Optoelectronic and Nanophotonics Research Laboratory(ONRL) Faculty of Electrical EngineeringSahand University of TechnologyTabrizIran

A new method based on phononic crystals is presented to detect the concentration of heavy water(D_(2)O)in an H_(2)O-D_(2)O *** have been obtained and analyzed in the concentration range of 0%-10%and 90%-100%D_(2)O.A proposed structure of tungsten scatterers in an aluminum host is *** order to detect the target material,a cavity region is considered as a sound wave resonator in which the target material with different concentrations of D_(2)O is *** changing the concentration of D_(2)O in the H_(2)O-D_(2)O mixture,the resonance frequency undergoes a frequency *** 1%change in D_(2)O concentration in the H_(2)O-D_(2)O mixture causes a frequency change of about 120 *** finite element method is used as the numerical method to calculate and analyze the natural frequencies and transmission spectra of the proposed *** performance evaluation index shows a high Q factor up to 1475758 and a high sensitivity up to 13075,which are acceptable values for sensing *** other figures of merit related to the detection performance also indicate high-quality performance of the designed sensor.

关键词： phononic crystals sensor H_(2)O-D_(2)O mixture cavity

Discrete Choice Models and Artificial Intelligence Techniques for Predicting the Determinants of Transport Mode Choice--A Systematic Review

在线全文

学校读者我要写书评

暂无评论

Computers, Materials & Continua 2024年第11期81卷 2161-2194页

作者： Mujahid ali Department of Transport Systems Traffic Engineering and LogisticsFaculty of Transport and Aviation EngineeringSilesian University of TechnologyKatowice40019Poland

Forecasting travel demand requires a grasp of individual decision-making ***,transport mode choice(TMC)is determined by personal and contextual factors that vary from person to *** characteristics have a substantial impact on travel behavior(TB),which makes it important to take into account while studying transport *** statistical techniques frequently presume linear correlations,but real-world data rarely follows these presumptions,which may make it harder to grasp the complex *** systematic review was conducted to examine how machine learning(ML)approaches might successfully capture nonlinear correlations that conventional methods may ignore to overcome such *** in-depth analysis of discrete choice models(DCM)and several ML algorithms,datasets,model validation strategies,and tuning techniques employed in previous research is carried out in the present ***,the current review also summarizes DCM and ML models to predict TMC and recognize the determinants of TB in an urban area for different transport *** two primary goals of our study are to establish the present conceptual frameworks for the factors influencing the TMC for daily activities and to pinpoint methodological issues and limitations in previous *** a total of 39 studies,our findings shed important light on the significance of considering factors that influence the *** adjusted kernel algorithms and hyperparameter-optimized ML algorithms outperform the typical ML ***(random forest),SVM(support vector machine),ANN(artificial neural network),and interpretable ML algorithms are the most widely used ML algorithms for the prediction of TMC where RF achieved an R2 of 0.95 and SVM achieved an accuracy of 93.18%;however,the adjusted kernel enhanced the accuracy of SVM 99.81%which shows that the interpretable algorithms outperformed the typical *** sensitivity analysis indicates that the most sign

关键词： Machine learning techniques AI transport mode choice discrete choice model sustainable transportation

Earthquake acceleration analysis using wavelet method

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Earthquake Engineering and Engineering Vibration 2021年第1期20卷 113-126页

作者： ali Heidari Noorollah Majidi Department of Civil Engineering University of ShahrekordShahrekordIran

There are several methods for analyzing the acceleration of an *** this research,a discrete wavelet theory based on the Mallat method was employed to analyze the acceleration of earthquake *** this purpose,first,the acceleration of the main earthquake was determined using the method of banding,filtering and correction of a filtered ***,the acceleration of the earthquake up to five stages was decomposed using discrete wavelet *** this method,in which the Down-Sampling rule is utilized in each step,the number of earthquake record points is half *** of the waveforms was based on the acceleration of the maximum original earthquake,and the maximum acceleration in all the waves was *** each of the five waves obtained from wavelet decomposition,the velocity curve and ground acceleration are obtained and compared with each ***,a structure was analyzed using the main wave of the earthquake and each of the waveforms was analyzed in five stages and their dynamic response curves were *** results showed that until the third stage of the wavelet decomposition,the error was insignificant and the dynamic response to the magnitude of the earthquake was *** analysis time is about 10% of the analysis time with the main wave,and the error is less than 6%.

关键词： accelerated earthquake mapping discrete wavelet dynamic analysis dynamic response