Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean...Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.展开更多
A broadband microstrip patch antenna, loaded E-U-shaped open slot on backward of radiating layer is proposed and experimentally investigated. The antenna employs a foam-filled dielectric substrate, whose dielectric co...A broadband microstrip patch antenna, loaded E-U-shaped open slot on backward of radiating layer is proposed and experimentally investigated. The antenna employs a foam-filled dielectric substrate, whose dielectric constant is within the lower end of the range. The proposed antenna has been designed for electromagnetic analysis including the impedance bandwidth, reflection coefficient, radiation pattern, and antenna gain. The open slot is loaded on the back radiated layer, which is perpendicular to the radiating edge of the oblong microstrip patch component, where the symmetric line feed is selected. This new technique used to increase the bandwidth and the gain of antenna through increasing current path by slot location, width and length on backward of radiating Layer. The main structure in this research was a single microstrip patch antenna planar with three layers operating at two resonant frequencies 4.440 GHz and 5.833 GHz. All the simulated results are confirmed by two packages of electromagnetism simulation. An impedance bandwidth (S11 ≤ ?10 dB) up to about 41.03% and 30.61% is achieved by individually optimizing its parameters. The antenna exhibits nearly stable radiation pattern with a maximum gains of 8.789 dBi and 9.966 dBi, which is suitable for Wi-Fi Band, satellite communications, and wireless presented. Whereas the results before this design that we have a proof of publication are 36.17% and 28.43%.展开更多
Fake reviews,also known as deceptive opinions,are used to mislead people and have gained more importance recently.This is due to the rapid increase in online marketing transactions,such as selling and purchasing.E-com...Fake reviews,also known as deceptive opinions,are used to mislead people and have gained more importance recently.This is due to the rapid increase in online marketing transactions,such as selling and purchasing.E-commerce provides a facility for customers to post reviews and comment about the product or service when purchased.New customers usually go through the posted reviews or comments on the website before making a purchase decision.However,the current challenge is how new individuals can distinguish truthful reviews from fake ones,which later deceives customers,inflicts losses,and tarnishes the reputation of companies.The present paper attempts to develop an intelligent system that can detect fake reviews on ecommerce platforms using n-grams of the review text and sentiment scores given by the reviewer.The proposed methodology adopted in this study used a standard fake hotel review dataset for experimenting and data preprocessing methods and a term frequency-Inverse document frequency(TF-IDF)approach for extracting features and their representation.For detection and classification,n-grams of review texts were inputted into the constructed models to be classified as fake or truthful.However,the experiments were carried out using four different supervised machine-learning techniques and were trained and tested on a dataset collected from the Trip Advisor website.The classification results of these experiments showed that na飗e Bayes(NB),support vector machine(SVM),adaptive boosting(AB),and random forest(RF)received 88%,93%,94%,and 95%,respectively,based on testing accuracy and tje F1-score.The obtained results were compared with existing works that used the same dataset,and the proposed methods outperformed the comparable methods in terms of accuracy.展开更多
Two wireless technologies, WiMAX based on IEEE standards and LTE standardized by 3GPP, are two competing technologies, nevertheless, are very technically similar. This competition started with the advent of their pre-...Two wireless technologies, WiMAX based on IEEE standards and LTE standardized by 3GPP, are two competing technologies, nevertheless, are very technically similar. This competition started with the advent of their pre-4G versions (802.16e for Mobile WiMAX and 3GPP release 8 for LTE) and continued with the advent of their 4G versions (WiMAX 2.0 based on IEEE 802.16 m and LTE-Advanced standardized by Release 10). It looks that the competition ended with the advantage of LTE. Plans are set for WiMAX to migrate/integrate with LTE in a multiple heterogeneous access technology mode. This article addresses the technical similarities and differences that advantage one technology over the other technology in order to determine which of these factors might have contributed to LTE winning. Nontechnical factors of commercial and historical nature which might also advantage one technology over the other one are also explored. Finally, current activities in the standardization of both WiMAX and LTE are presented with a perspective on the prospects of both technologies.展开更多
This article aims to assess health habits,safety behaviors,and anxiety factors in the community during the novel coronavirus disease(COVID-19)pandemic in Saudi Arabia based on primary data collected through a question...This article aims to assess health habits,safety behaviors,and anxiety factors in the community during the novel coronavirus disease(COVID-19)pandemic in Saudi Arabia based on primary data collected through a questionnaire with 320 respondents.In other words,this paper aims to provide empirical insights into the correlation and the correspondence between sociodemographic factors(gender,nationality,age,citizenship factors,income,and education),and psycho-behavioral effects on individuals in response to the emergence of this new pandemic.To focus on the interaction between these variables and their effects,we suggest different methods of analysis,comprising regression trees and support vector machine regression(SVMR)algorithms.According to the regression tree results,the age variable plays a predominant role in health habits,safety behaviors,and anxiety.The health habit index,which focuses on the extent of behavioral change toward the commitment to use the health and protection methods,is highly affected by gender and age factors.The average monthly income is also a relevant factor but has contrasting effects during the COVID-19 pandemic period.The results of the SVMR model reveal a strong positive effect of income,with R^(2) values of 99.59%,99.93%and 99.88%corresponding to health habits,safety behaviors,and anxiety.展开更多
Accurate significant wave height(SWH)prediction is essential for the development and utilization of wave energy.Deep learning methods such as recurrent and convolutional neural networks have achieved good results in S...Accurate significant wave height(SWH)prediction is essential for the development and utilization of wave energy.Deep learning methods such as recurrent and convolutional neural networks have achieved good results in SWH forecasting.However,these methods do not adapt well to dynamic seasonal variations in wave data.In this study,we propose a novel method—the spatiotemporal dynamic graph(STDG)neural network.This method predicts the SWH of multiple nodes based on dynamic graph modeling and multi-characteristic fusion.First,considering the dynamic seasonal variations in the wave direction over time,the network models wave dynamic spatial dependencies from long-and short-term pattern perspectives.Second,to correlate multiple characteristics with SWH,the network introduces a cross-characteristic transformer to effectively fuse multiple characteristics.Finally,we conducted experiments on two datasets from the South China Sea and East China Sea to validate the proposed method and compared it with five prediction methods in the three categories.The experimental results show that the proposed method achieves the best performance at all predictive scales and has greater advantages for extreme value prediction.Furthermore,an analysis of the dynamic graph shows that the proposed method captures the seasonal variation mechanism of the waves.展开更多
An efficient integration of electrochromic and electrochemical devices into one flexible entity enables both energy storage and energy-saving dual-functionalities.For this purpose,achieving both high electrochromic an...An efficient integration of electrochromic and electrochemical devices into one flexible entity enables both energy storage and energy-saving dual-functionalities.For this purpose,achieving both high electrochromic and electrochemical performance is the key aspect.Herein,a new 3D architecture is successfully made by knotting W_(17)O_(47)@PEDOT(poly(3,4-ethylenedioxythiophene)):PSS(poly(styrenesulfonate))nanowires with NaWO_(3)nanoknots,and interestingly,the 3D W_(17)O_(47)/(NaWO_(3)-knots)@PEDOT:PSS cathode thus-made simultaneously exhibits a large optical modulation(79.7%at 633 nm),an ultra-long cycling life(76%of original optical modulation retained after 12400 cycles),and a high areal capacitance(55.1 mF cm^(-2)at 0.1 mA cm^(-2)).Our density functional theory(DFT)calculations demonstrate that the much improved dual-functional performance is correlated to the raised electronic conductivity and ion adsorption at the W_(17)O_(47)/(NaWO_(3)nanoknots)interface,together with the ion adsorption of PEDOT:PSS in the 3D-knotted architecture.As a proof-of-concept application,different-sized flexible dual-functional electrochromic/electrochemical devices(FDEDs)were assembled and investigated for various application scenarios,including a smart window(15 cm×10 cm),a wearable wristband(20 cm×2.5 cm),and a smart eyeglass.The smart window made of the FDED enables a large temperature difference of 27.6℃ confirm-tested in model houses,where the energy source also powers three light-emitting diodes(LEDs).The understandings of the key governing principles in the electrodes and dual-functionalities provide a timely foundation for the new generation flexible multifunctional devices.展开更多
Multifunctional electrochromic-induced rechargeable aqueous batteries(MERABs) integrate electrochromism and aqueous ion batteries into one platform, which is able to deliver the conversion and storage of photo-thermal...Multifunctional electrochromic-induced rechargeable aqueous batteries(MERABs) integrate electrochromism and aqueous ion batteries into one platform, which is able to deliver the conversion and storage of photo-thermal-electrochemical sources.Aqueous ion batteries compensate for the drawbacks of slow kinetic reactions and unsatisfied storage capacities of electrochromic devices. On the other hand, electrochromic technology can enable dynamically regulation of solar light and heat radiation. However,MERABs still face several technical issues, including a trade-off between electrochromic and electrochemical performance, low conversion efficiency and poor service life. In this connection, novel device configuration and electrode materials, and an optimized compatibility need to be considered for multidisciplinary applications. In this review,the unique advantages, key challenges and advanced applications are elucidated in a timely and comprehensive manner. Firstly, the prerequisites for effective integration of the working mechanism and device configuration, as well as the choice of electrode materials are examined. Secondly, the latest advances in the applications of MERABs are discussed, including wearable, self-powered, integrated systems and multisystem conversion. Finally, perspectives on the current challenges and future development are outlined, highlighting the giant leap required from laboratory prototypes to large-scale production and eventual commercialization.展开更多
In this paper,we propose a stochastic level-value estimation method to solve a kind of box-constrained global optimization problem.For this purpose,we first derive a generalized variance function associated with the c...In this paper,we propose a stochastic level-value estimation method to solve a kind of box-constrained global optimization problem.For this purpose,we first derive a generalized variance function associated with the considered problem and prove that the largest root of the function is the global minimal value.Then,Newton’s method is applied to find the root.The convergence of the proposed method is established under some suitable conditions.Based on the main idea of the cross-entropy method to update the sampling density function,an important sampling technique is proposed in the implementation.Preliminary numerical experiments indicate the validity of the proposed method.展开更多
基金The National Key R&D Program of China under contract No.2021YFC3101603.
文摘Ocean temperature is an important physical variable in marine ecosystems,and ocean temperature prediction is an important research objective in ocean-related fields.Currently,one of the commonly used methods for ocean temperature prediction is based on data-driven,but research on this method is mostly limited to the sea surface,with few studies on the prediction of internal ocean temperature.Existing graph neural network-based methods usually use predefined graphs or learned static graphs,which cannot capture the dynamic associations among data.In this study,we propose a novel dynamic spatiotemporal graph neural network(DSTGN)to predict threedimensional ocean temperature(3D-OT),which combines static graph learning and dynamic graph learning to automatically mine two unknown dependencies between sequences based on the original 3D-OT data without prior knowledge.Temporal and spatial dependencies in the time series were then captured using temporal and graph convolutions.We also integrated dynamic graph learning,static graph learning,graph convolution,and temporal convolution into an end-to-end framework for 3D-OT prediction using time-series grid data.In this study,we conducted prediction experiments using high-resolution 3D-OT from the Copernicus global ocean physical reanalysis,with data covering the vertical variation of temperature from the sea surface to 1000 m below the sea surface.We compared five mainstream models that are commonly used for ocean temperature prediction,and the results showed that the method achieved the best prediction results at all prediction scales.
文摘A broadband microstrip patch antenna, loaded E-U-shaped open slot on backward of radiating layer is proposed and experimentally investigated. The antenna employs a foam-filled dielectric substrate, whose dielectric constant is within the lower end of the range. The proposed antenna has been designed for electromagnetic analysis including the impedance bandwidth, reflection coefficient, radiation pattern, and antenna gain. The open slot is loaded on the back radiated layer, which is perpendicular to the radiating edge of the oblong microstrip patch component, where the symmetric line feed is selected. This new technique used to increase the bandwidth and the gain of antenna through increasing current path by slot location, width and length on backward of radiating Layer. The main structure in this research was a single microstrip patch antenna planar with three layers operating at two resonant frequencies 4.440 GHz and 5.833 GHz. All the simulated results are confirmed by two packages of electromagnetism simulation. An impedance bandwidth (S11 ≤ ?10 dB) up to about 41.03% and 30.61% is achieved by individually optimizing its parameters. The antenna exhibits nearly stable radiation pattern with a maximum gains of 8.789 dBi and 9.966 dBi, which is suitable for Wi-Fi Band, satellite communications, and wireless presented. Whereas the results before this design that we have a proof of publication are 36.17% and 28.43%.
文摘Fake reviews,also known as deceptive opinions,are used to mislead people and have gained more importance recently.This is due to the rapid increase in online marketing transactions,such as selling and purchasing.E-commerce provides a facility for customers to post reviews and comment about the product or service when purchased.New customers usually go through the posted reviews or comments on the website before making a purchase decision.However,the current challenge is how new individuals can distinguish truthful reviews from fake ones,which later deceives customers,inflicts losses,and tarnishes the reputation of companies.The present paper attempts to develop an intelligent system that can detect fake reviews on ecommerce platforms using n-grams of the review text and sentiment scores given by the reviewer.The proposed methodology adopted in this study used a standard fake hotel review dataset for experimenting and data preprocessing methods and a term frequency-Inverse document frequency(TF-IDF)approach for extracting features and their representation.For detection and classification,n-grams of review texts were inputted into the constructed models to be classified as fake or truthful.However,the experiments were carried out using four different supervised machine-learning techniques and were trained and tested on a dataset collected from the Trip Advisor website.The classification results of these experiments showed that na飗e Bayes(NB),support vector machine(SVM),adaptive boosting(AB),and random forest(RF)received 88%,93%,94%,and 95%,respectively,based on testing accuracy and tje F1-score.The obtained results were compared with existing works that used the same dataset,and the proposed methods outperformed the comparable methods in terms of accuracy.
文摘Two wireless technologies, WiMAX based on IEEE standards and LTE standardized by 3GPP, are two competing technologies, nevertheless, are very technically similar. This competition started with the advent of their pre-4G versions (802.16e for Mobile WiMAX and 3GPP release 8 for LTE) and continued with the advent of their 4G versions (WiMAX 2.0 based on IEEE 802.16 m and LTE-Advanced standardized by Release 10). It looks that the competition ended with the advantage of LTE. Plans are set for WiMAX to migrate/integrate with LTE in a multiple heterogeneous access technology mode. This article addresses the technical similarities and differences that advantage one technology over the other technology in order to determine which of these factors might have contributed to LTE winning. Nontechnical factors of commercial and historical nature which might also advantage one technology over the other one are also explored. Finally, current activities in the standardization of both WiMAX and LTE are presented with a perspective on the prospects of both technologies.
文摘This article aims to assess health habits,safety behaviors,and anxiety factors in the community during the novel coronavirus disease(COVID-19)pandemic in Saudi Arabia based on primary data collected through a questionnaire with 320 respondents.In other words,this paper aims to provide empirical insights into the correlation and the correspondence between sociodemographic factors(gender,nationality,age,citizenship factors,income,and education),and psycho-behavioral effects on individuals in response to the emergence of this new pandemic.To focus on the interaction between these variables and their effects,we suggest different methods of analysis,comprising regression trees and support vector machine regression(SVMR)algorithms.According to the regression tree results,the age variable plays a predominant role in health habits,safety behaviors,and anxiety.The health habit index,which focuses on the extent of behavioral change toward the commitment to use the health and protection methods,is highly affected by gender and age factors.The average monthly income is also a relevant factor but has contrasting effects during the COVID-19 pandemic period.The results of the SVMR model reveal a strong positive effect of income,with R^(2) values of 99.59%,99.93%and 99.88%corresponding to health habits,safety behaviors,and anxiety.
基金The National Key R&D Program of China under contract No.2021YFC3101604。
文摘Accurate significant wave height(SWH)prediction is essential for the development and utilization of wave energy.Deep learning methods such as recurrent and convolutional neural networks have achieved good results in SWH forecasting.However,these methods do not adapt well to dynamic seasonal variations in wave data.In this study,we propose a novel method—the spatiotemporal dynamic graph(STDG)neural network.This method predicts the SWH of multiple nodes based on dynamic graph modeling and multi-characteristic fusion.First,considering the dynamic seasonal variations in the wave direction over time,the network models wave dynamic spatial dependencies from long-and short-term pattern perspectives.Second,to correlate multiple characteristics with SWH,the network introduces a cross-characteristic transformer to effectively fuse multiple characteristics.Finally,we conducted experiments on two datasets from the South China Sea and East China Sea to validate the proposed method and compared it with five prediction methods in the three categories.The experimental results show that the proposed method achieves the best performance at all predictive scales and has greater advantages for extreme value prediction.Furthermore,an analysis of the dynamic graph shows that the proposed method captures the seasonal variation mechanism of the waves.
基金Shanghai Municipal Education Commission,Grant/Award Number:2019-01-07-00-09-E00020Shanghai Municipal Science and Technology Commission,Grant/Award Number:18JC1412800Singapore Ministry of Education,Grant/Award Number:MOE2018-T2-2-095。
文摘An efficient integration of electrochromic and electrochemical devices into one flexible entity enables both energy storage and energy-saving dual-functionalities.For this purpose,achieving both high electrochromic and electrochemical performance is the key aspect.Herein,a new 3D architecture is successfully made by knotting W_(17)O_(47)@PEDOT(poly(3,4-ethylenedioxythiophene)):PSS(poly(styrenesulfonate))nanowires with NaWO_(3)nanoknots,and interestingly,the 3D W_(17)O_(47)/(NaWO_(3)-knots)@PEDOT:PSS cathode thus-made simultaneously exhibits a large optical modulation(79.7%at 633 nm),an ultra-long cycling life(76%of original optical modulation retained after 12400 cycles),and a high areal capacitance(55.1 mF cm^(-2)at 0.1 mA cm^(-2)).Our density functional theory(DFT)calculations demonstrate that the much improved dual-functional performance is correlated to the raised electronic conductivity and ion adsorption at the W_(17)O_(47)/(NaWO_(3)nanoknots)interface,together with the ion adsorption of PEDOT:PSS in the 3D-knotted architecture.As a proof-of-concept application,different-sized flexible dual-functional electrochromic/electrochemical devices(FDEDs)were assembled and investigated for various application scenarios,including a smart window(15 cm×10 cm),a wearable wristband(20 cm×2.5 cm),and a smart eyeglass.The smart window made of the FDED enables a large temperature difference of 27.6℃ confirm-tested in model houses,where the energy source also powers three light-emitting diodes(LEDs).The understandings of the key governing principles in the electrodes and dual-functionalities provide a timely foundation for the new generation flexible multifunctional devices.
基金support by Shanghai Municipal Education Commission (No. 2019-01-07-00-09E00020), for research conducted at the Shanghai Universitysupport by Independent depolyment project of Qinghai Institute of Salt Lakes, Chinese Academy of Sciences (E260GC0401)support by the Singapore National Research Foundation (NRF-CRP26-2021-0003, NRF), for research conducted at the National University of Singapore。
文摘Multifunctional electrochromic-induced rechargeable aqueous batteries(MERABs) integrate electrochromism and aqueous ion batteries into one platform, which is able to deliver the conversion and storage of photo-thermal-electrochemical sources.Aqueous ion batteries compensate for the drawbacks of slow kinetic reactions and unsatisfied storage capacities of electrochromic devices. On the other hand, electrochromic technology can enable dynamically regulation of solar light and heat radiation. However,MERABs still face several technical issues, including a trade-off between electrochromic and electrochemical performance, low conversion efficiency and poor service life. In this connection, novel device configuration and electrode materials, and an optimized compatibility need to be considered for multidisciplinary applications. In this review,the unique advantages, key challenges and advanced applications are elucidated in a timely and comprehensive manner. Firstly, the prerequisites for effective integration of the working mechanism and device configuration, as well as the choice of electrode materials are examined. Secondly, the latest advances in the applications of MERABs are discussed, including wearable, self-powered, integrated systems and multisystem conversion. Finally, perspectives on the current challenges and future development are outlined, highlighting the giant leap required from laboratory prototypes to large-scale production and eventual commercialization.
文摘In this paper,we propose a stochastic level-value estimation method to solve a kind of box-constrained global optimization problem.For this purpose,we first derive a generalized variance function associated with the considered problem and prove that the largest root of the function is the global minimal value.Then,Newton’s method is applied to find the root.The convergence of the proposed method is established under some suitable conditions.Based on the main idea of the cross-entropy method to update the sampling density function,an important sampling technique is proposed in the implementation.Preliminary numerical experiments indicate the validity of the proposed method.
