With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order ...With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.展开更多
Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to ...Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.展开更多
Municipal civil engineering is the key content of municipal construction,and the construction scale is usually large.The quality of the project plays an important role in the development of urban economy.Due to the ra...Municipal civil engineering is the key content of municipal construction,and the construction scale is usually large.The quality of the project plays an important role in the development of urban economy.Due to the rapid increase of high-rise buildings,skyscrapers and underground buildings,the construction technology of deep foundation pit support has gradually become an indispensable construction technology.Therefore,the selection of foundation pit support construction technology is crucial in ensuring that whether the foundation is firm and stable,and whether the subsequent construction activities can be carried out smoothly.In view of this,the article discusses the application of deep foundation pit support construction technology in municipal civil engineering,aiming to provide reference for subsequent projects.展开更多
Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example t...Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example to analyze deep foundation pit excavation technology,including the nature of this construction project,the main technical measures in the construction of deep foundation pit,and the analysis of the safety risk prevention and control measures.The purpose of this analysis is to provide scientific reference for the construction quality and safety of deep foundation pits.展开更多
This paper introduces a Convolutional Neural Network (CNN) model for Arabic Sign Language (AASL) recognition, using the AASL dataset. Recognizing the fundamental importance of communication for the hearing-impaired, e...This paper introduces a Convolutional Neural Network (CNN) model for Arabic Sign Language (AASL) recognition, using the AASL dataset. Recognizing the fundamental importance of communication for the hearing-impaired, especially within the Arabic-speaking deaf community, the study emphasizes the critical role of sign language recognition systems. The proposed methodology achieves outstanding accuracy, with the CNN model reaching 99.9% accuracy on the training set and a validation accuracy of 97.4%. This study not only establishes a high-accuracy AASL recognition model but also provides insights into effective dropout strategies. The achieved high accuracy rates position the proposed model as a significant advancement in the field, holding promise for improved communication accessibility for the Arabic-speaking deaf community.展开更多
The main electrical properties of advanced Silicon On Insulator MOSFETs are addressed. The subthreshold and high field operations are analysed as a function of device architecture. The special SOI parasitic phenomena,...The main electrical properties of advanced Silicon On Insulator MOSFETs are addressed. The subthreshold and high field operations are analysed as a function of device architecture. The special SOI parasitic phenomena, such as the floating body potential and temperature, are critically reviewed. The main limitations of submicron MOSFET are comparatively evaluated for various SOI structures. Short channel and hot carrier effects as well as the reliability of the SOI technology are investigated for gate length down to sub\|0 1 micron.展开更多
1 Introduction The Paleogene strata(with a depth of more than 2500m)in the Bohai sea is complex(Xu Changgui,2006),the reservoir buried deeply,the reservoir prediction is difficult(LAI Weicheng,XU Changgui,2012),and
On December 9, 2014 the scientific research project ＂Developmentand commercial application of technology forultra-deep HDS of diesel （RTS）＂ jointly performed bythe SINOPEC Research Institute of Petroleum Processin...On December 9, 2014 the scientific research project ＂Developmentand commercial application of technology forultra-deep HDS of diesel （RTS）＂ jointly performed bythe SINOPEC Research Institute of Petroleum Processing（RIPP）, the Yanshan Petrochemical Branch Company（YPBC）, the Maoming Petrochemical Branch Companyand the Guangzhou Petrochemical Branch Company haspassed in Beijing the technical appraisal organized by theScience and Technology Division of the Sinopec Corp.展开更多
Privacy and trust are significant issues in intelligent transportation systems(ITS).Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless...Privacy and trust are significant issues in intelligent transportation systems(ITS).Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels,optical fiber,and blockchain technology.The Internet of Things(IoT)is a network of connected,interconnected gadgets.Privacy issues occasionally arise due to the amount of data generated.However,they have been primarily addressed by blockchain and smart contract technology.While there are still security issues with smart contracts,primarily due to the complexity of writing the code,there are still many challenges to consider when designing blockchain designs for the IoT environment.This study uses traditional blockchain technology with the“You Only Look Once”(YOLO)object detection method to accurately locate and identify license plates.While YOLO and blockchain technologies used for intelligent vehicle license plate recognition are promising,they have received limited research attention.Real-time object identification and recognition would be possible by combining a cutting-edge object detection technique with a regional convolutional neural network(RCNN)built with the tensor flow core open source libraries.This method works reasonably well for identifying any license plate.The Automatic License Plate Recognition(ALPR)approach delivered outstanding results in various datasets.First,with a recognition rate of 96.2%,our system(UFPR-ALPR)surpassed the previously used technology,consisting of 4500 frames and around 150 films.Second,a deep learning algorithm was trained to recognize images of license plate numbers using the UFPR-ALPR dataset.Third,the license plate’s characters were complicated for standard methods to identify because of the shifting lighting correctly.The proposed model,however,produced beneficial outcomes.展开更多
Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology th...Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human beings.In the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital applications.The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 environment.The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification.Primarily,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based encryption.The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images.The secret images,encrypted by signcryption technique,are embedded into cover images.Besides,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax classifier.The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication.The proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects.The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.展开更多
Ultra-deep formations in China contain rich hydrocarbon resources.In recent years,the number of ultradeep wells has been continuously increasing.However,efforts to facilitate tlte drilling and exploration of these ult...Ultra-deep formations in China contain rich hydrocarbon resources.In recent years,the number of ultradeep wells has been continuously increasing.However,efforts to facilitate tlte drilling and exploration of these ultra-deep reservoirs are facing many challenges,such as complicated formation pressures,complicated formation lithologic features,complicated formation fluids,difficulties in the accurate calculation of formation parameters,difficulties in borehole structure design optimization,instabilities in the performances of drilling fluid and key cementing materials/systems,high temperature-resistance and pressure-resistance requirements for downhole tools and instruments,complicated engineering problems,and slow drilling speeds.Under such circumstances,it is very difficult to ensure the performance of such drilling operations.In order to address these challenges,SINOPEC has developed relevant drilling technologies for ultra-deep wells in complicated geological conditions through intensive research on accurate descriptions of complex geologic characteristics,borehole structure design optimization,fast drilling techniques for deep and hard formations,temperature-resistant highdensity drilling fluid,anti-channeling cementing in high-pressure gas wells,borehole trajectory control in ultra-deep horizontal wells and other key technologies.These technologies can provide sound engineering and technical support for tlte exploration and development of hydrocarbon resources in ultra-deep formations in China.展开更多
In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repe...In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.展开更多
文摘With a reduction in transistor dimensions to the nanoscale regime of 45 nm or less, quantum mechanical effects begin to reveal themselves and have an impact on key device performance parameters. As a result, in order to develop simulation tools that can be used for the design of nanoscale transistors in the future, new theories and modelling methodologies must be developed that properly and effectively capture the physics of quantum transport. An artificial neural network(ANN) is used in this paper to examine nanoscale CMOS circuits and predict the performance parameters of CMOS-based digital inverters for a temperature range of 300 K to 400 K. The training algorithm included three hidden layers with sizes of 20, 10, and 8, as well as a function fitting ANN with Bayesian Backpropagation Regularization. Further, simulation through HSPICE using Predictive Technology Model(PTM) nominal parameters has been done to compare with ANN(trained using an analytical model) results. The obtained results lie within the acceptable range of 1%-10%. Moreover, it has also been demonstrated that the ANN simulation provides a speed improvement of around 85 % over the HSPICE simulation, and that it can be easily integrated into software tools for designing and simulating complicated CMOS logic circuits.
文摘Voltage scaling has been extensively used in industry for decades to reduce power consumption.In recent years,exploring digital circuit operation in moderate inversion has created an interest among researchers due to its immense capability to provide a perfect tradeoff between high performance and low energy operation.But circuits operating in moderate inversion are susceptible to process variations and variability.To compute variability,statistical parameters such as the probability density function(PDF)and cumulative distribution function(CDF)are required.This paper presents an analytical model framework for delay calculations utilizing log skew normal distribution for ultradeep submicron technology nodes up to 22 nm.The CDF of the proposed model is utilized to calculate minimum and maximum delays with 3σ-accuracy providing better accuracy than the conventional methods.The obtained results are also compared with Monte Carlo simulations with errors lying within the acceptable range of 2%-4%.
文摘Municipal civil engineering is the key content of municipal construction,and the construction scale is usually large.The quality of the project plays an important role in the development of urban economy.Due to the rapid increase of high-rise buildings,skyscrapers and underground buildings,the construction technology of deep foundation pit support has gradually become an indispensable construction technology.Therefore,the selection of foundation pit support construction technology is crucial in ensuring that whether the foundation is firm and stable,and whether the subsequent construction activities can be carried out smoothly.In view of this,the article discusses the application of deep foundation pit support construction technology in municipal civil engineering,aiming to provide reference for subsequent projects.
文摘Deep foundation pit excavation is a basic and key step involved in modern building construction.In order to ensure the construction quality and safety of deep foundation pits,this paper takes a project as an example to analyze deep foundation pit excavation technology,including the nature of this construction project,the main technical measures in the construction of deep foundation pit,and the analysis of the safety risk prevention and control measures.The purpose of this analysis is to provide scientific reference for the construction quality and safety of deep foundation pits.
文摘This paper introduces a Convolutional Neural Network (CNN) model for Arabic Sign Language (AASL) recognition, using the AASL dataset. Recognizing the fundamental importance of communication for the hearing-impaired, especially within the Arabic-speaking deaf community, the study emphasizes the critical role of sign language recognition systems. The proposed methodology achieves outstanding accuracy, with the CNN model reaching 99.9% accuracy on the training set and a validation accuracy of 97.4%. This study not only establishes a high-accuracy AASL recognition model but also provides insights into effective dropout strategies. The achieved high accuracy rates position the proposed model as a significant advancement in the field, holding promise for improved communication accessibility for the Arabic-speaking deaf community.
文摘The main electrical properties of advanced Silicon On Insulator MOSFETs are addressed. The subthreshold and high field operations are analysed as a function of device architecture. The special SOI parasitic phenomena, such as the floating body potential and temperature, are critically reviewed. The main limitations of submicron MOSFET are comparatively evaluated for various SOI structures. Short channel and hot carrier effects as well as the reliability of the SOI technology are investigated for gate length down to sub\|0 1 micron.
基金funded by Major Projects of National Science and Technology “Large Oil and Gas Fields and CBM development”(Grant No. 2016ZX05 027)
文摘1 Introduction The Paleogene strata(with a depth of more than 2500m)in the Bohai sea is complex(Xu Changgui,2006),the reservoir buried deeply,the reservoir prediction is difficult(LAI Weicheng,XU Changgui,2012),and
文摘On December 9, 2014 the scientific research project ＂Developmentand commercial application of technology forultra-deep HDS of diesel （RTS）＂ jointly performed bythe SINOPEC Research Institute of Petroleum Processing（RIPP）, the Yanshan Petrochemical Branch Company（YPBC）, the Maoming Petrochemical Branch Companyand the Guangzhou Petrochemical Branch Company haspassed in Beijing the technical appraisal organized by theScience and Technology Division of the Sinopec Corp.
基金Project supported by the National Natural Science Foundation of China （Grant No 60206006）. the Program for New Century Excellent Talents of Ministry of Education of China （Grant No 681231366）. the National Defense Pre-Research Foundation of China （Grant No 51408010305DZ0168） and the Key Project of Chinese Ministry of Education （Grant No 104172）.
基金extend their appreciation to the deanship of scientific research at Shaqra University for funding this research work through the Project Number(SU-ANN-202248).
文摘Privacy and trust are significant issues in intelligent transportation systems(ITS).Data security is critical in ITS systems since sensitive user data is communicated to another user over the internet through wireless devices and routes such as radio channels,optical fiber,and blockchain technology.The Internet of Things(IoT)is a network of connected,interconnected gadgets.Privacy issues occasionally arise due to the amount of data generated.However,they have been primarily addressed by blockchain and smart contract technology.While there are still security issues with smart contracts,primarily due to the complexity of writing the code,there are still many challenges to consider when designing blockchain designs for the IoT environment.This study uses traditional blockchain technology with the“You Only Look Once”(YOLO)object detection method to accurately locate and identify license plates.While YOLO and blockchain technologies used for intelligent vehicle license plate recognition are promising,they have received limited research attention.Real-time object identification and recognition would be possible by combining a cutting-edge object detection technique with a regional convolutional neural network(RCNN)built with the tensor flow core open source libraries.This method works reasonably well for identifying any license plate.The Automatic License Plate Recognition(ALPR)approach delivered outstanding results in various datasets.First,with a recognition rate of 96.2%,our system(UFPR-ALPR)surpassed the previously used technology,consisting of 4500 frames and around 150 films.Second,a deep learning algorithm was trained to recognize images of license plate numbers using the UFPR-ALPR dataset.Third,the license plate’s characters were complicated for standard methods to identify because of the shifting lighting correctly.The proposed model,however,produced beneficial outcomes.
基金The authors extend their appreciation to the Deanship of Scientific Research at King Khalid University for funding this work through the small Groups Project under grant number(168/43)Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2022R151),Princess Nourah bint Abdulrahman University,Riyadh,Saudi ArabiaThe authors would like to thank the Deanship of Scientific Research at Umm Al-Qura University for supporting this work by Grant Code:(22UQU4310373DSR59).
文摘Emerging technologies such as edge computing,Internet of Things(IoT),5G networks,big data,Artificial Intelligence(AI),and Unmanned Aerial Vehicles(UAVs)empower,Industry 4.0,with a progressive production methodology that shows attention to the interaction between machine and human beings.In the literature,various authors have focused on resolving security problems in UAV communication to provide safety for vital applications.The current research article presents a Circle Search Optimization with Deep Learning Enabled Secure UAV Classification(CSODL-SUAVC)model for Industry 4.0 environment.The suggested CSODL-SUAVC methodology is aimed at accomplishing two core objectives such as secure communication via image steganography and image classification.Primarily,the proposed CSODL-SUAVC method involves the following methods such as Multi-Level Discrete Wavelet Transformation(ML-DWT),CSO-related Optimal Pixel Selection(CSO-OPS),and signcryption-based encryption.The proposed model deploys the CSO-OPS technique to select the optimal pixel points in cover images.The secret images,encrypted by signcryption technique,are embedded into cover images.Besides,the image classification process includes three components namely,Super-Resolution using Convolution Neural Network(SRCNN),Adam optimizer,and softmax classifier.The integration of the CSO-OPS algorithm and Adam optimizer helps in achieving the maximum performance upon UAV communication.The proposed CSODLSUAVC model was experimentally validated using benchmark datasets and the outcomes were evaluated under distinct aspects.The simulation outcomes established the supreme better performance of the CSODL-SUAVC model over recent approaches.
基金Key National Science and Technology Development Project for the"Twelfth Five-year Plan"-"Development of large-scale oil/gas fields and coalbed methane(CBM)",Subtopic 6:"Key technology for boreholes of oil/gas producers in marine carbonate rocks"(No.:2011ZX05005-006)
文摘Ultra-deep formations in China contain rich hydrocarbon resources.In recent years,the number of ultradeep wells has been continuously increasing.However,efforts to facilitate tlte drilling and exploration of these ultra-deep reservoirs are facing many challenges,such as complicated formation pressures,complicated formation lithologic features,complicated formation fluids,difficulties in the accurate calculation of formation parameters,difficulties in borehole structure design optimization,instabilities in the performances of drilling fluid and key cementing materials/systems,high temperature-resistance and pressure-resistance requirements for downhole tools and instruments,complicated engineering problems,and slow drilling speeds.Under such circumstances,it is very difficult to ensure the performance of such drilling operations.In order to address these challenges,SINOPEC has developed relevant drilling technologies for ultra-deep wells in complicated geological conditions through intensive research on accurate descriptions of complex geologic characteristics,borehole structure design optimization,fast drilling techniques for deep and hard formations,temperature-resistant highdensity drilling fluid,anti-channeling cementing in high-pressure gas wells,borehole trajectory control in ultra-deep horizontal wells and other key technologies.These technologies can provide sound engineering and technical support for tlte exploration and development of hydrocarbon resources in ultra-deep formations in China.
文摘In recent years,AI(artificial intelligence)has made considerable strides,transforming a number of industries and facets of daily life.However,as AI develops more,worries about its potential dangers and unforeseen repercussions have surfaced.This article investigates the claim that AI technology has broken free from human control and is now unstoppable.We look at how AI is developing right now,what it means for society,and what steps are being taken to reduce the risks that come with it.We seek to highlight the need for responsible development and implementation of this game-changing technology by examining the opportunities and challenges that AI presents.
